Trabajos babysitting en Reino Unido

Help us make a big green dent in the universe. We're on a mission to drive the global renewable energy revolution, and we need many more people to help us make our vision a reality. Octopus Energy Generation (OEGEN) is a leader in sourcing, investing in, and managing a wide range of utility-scale renewable energy assets. As we continue to expand our investment base, we are dedicated to building a diverse team that reflects the communities we serve. Currently, we manage a global portfolio of over £8 billion in renewable energy assets. We are committed to delivering best-in-class responsible investment activity, offering like-minded investors the means and products to invest their capital sustainably. It is our ambition to change the entire energy lifecycle and make every green electron matter, delivering the best outcomes for customers, investors, the environment and society, accelerating the transition to net zero. We are embarking on a comprehensive transformation program designed to drive significant advancements in our business operations and technology landscape. Our primary goal is to transition from our current reliance on legacy systems and specialized off-the-shelf tools to a more integrated, AI-driven, and data-centric operational model. Leveraging insights and guidance from our other technically mature entities like Kraken and OE, we plan to adopt cutting-edge tools and capabilities, particularly in AI and Python-driven solutions. By investing in a diverse range of skills, we aim to create a hybrid team capable of operating in both our legacy and future environments, ultimately transforming OEGEN into an efficient, data-driven organization. The tools are already here. Like the rest of OE Group, OEGEN runs on Databricks, we're moving onto our own Microsoft 365 tenant, and Octopus Energy Group gives us access to a powerful set of shared data and AI capabilities. What we're missing is someone whose job is to make all of it work together for our Fund Management business - and then build genuinely useful things on top of it. This is a two-sided role. On one side, you'll integrate: wiring third-party systems, internal apps and document storage into the environment we already have, setting sensible guardrails around access and cost, and adopting existing Group capability wherever it does the job rather than rebuilding it. On the other, you'll build: turning those connections into data products, internal tools and AI-enabled workflows that fund management, asset management and finance use every day. Tying the two together, you'll develop and own the playbook - the documented, repeatable patterns for how a new system gets connected, how a tool gets built and shipped, and how both get supported afterwards - so that what you learn once becomes how the whole team works. The two halves feed each other: you'll understand what's possible because you built the plumbing, and you'll build better plumbing because you know what people actually do with it. Integrate the systems our business runs on - third-party providers, internal tools, our own SharePoint and Microsoft 365 tenant - into our existing Databricks environment, via APIs and existing connectors. Build data products on top of what you connect: well-modelled, documented, reusable datasets that the business consumes directly through Excel, dashboards and natural-language querying, rather than one-off extracts. Design and ship internal applications and AI-enabled tools - using Python, Streamlit, Databricks Apps (HTMX), Lakebase, FastAPI or similar - that put data and AI directly into the hands of fund management, asset management and finance teams. Prototype, evaluate and productionise new AI capability, from document AI and retrieval to agentic workflows, and turn the ideas that prove out into supported products rather than abandoned experiments. Take an adopt-first approach: work with Octopus Energy Group's data platform and AI teams to reuse capability that already exists, and configure it for OEGEN rather than building parallel versions of it. Set up practical guardrails inside Databricks and Unity Catalog - schema and workspace access, permissions, environment hygiene - so more teams can use it without stepping on each other. Bring cost management from reactive to proactive: tagging, budgets, alerting and usage monitoring, so Databricks and AI token spend can be attributed to the right team, project or fund before the invoice arrives. Get our AI usage properly credentialed and logged - managed keys and access rather than API keys sitting in individual password managers - and provide clean patterns for embedding AI into the tools we build. Standardise how we build and ship internal apps: shared templates, authentication, deployment and documentation, so a tool remains supportable by someone other than the person who wrote it. Consolidate the ad-hoc scripts, spreadsheets and no-code workflows we've accumulated into fewer, better-understood integrations that don't need babysitting, and automate the repetitive parts of our own workflow. Work directly with non-technical teams to understand their problems and translate them into things we can build. Strong systems integration experience - connecting business systems, SaaS tools and data sources via REST APIs, connectors and authentication flows. A track record of building and shipping data products or internal applications that people actually use, not just pipelines that feed someone else's reports. Solid Python and SQL, used daily for building, automation and data modelling. Hands-on experience with a cloud data platform in production (Databricks preferred): workspaces, catalogs, permissions and compute. Practical experience integrating AI into real tools - LLM APIs, retrieval, agents - with a clear-eyed sense of what works and what's still a demo. Practical identity and access experience - SSO, service accounts, credential management and access lifecycle - enough to make sensible, secure choices without a security team holding your hand. Experience with Microsoft 365 / SharePoint integration, or a comparable enterprise document and collaboration stack. Real experience keeping cloud or AI usage costs under control: you know what drives the bill and how to attribute and cap it. A pragmatist's instinct for adopting over building where infrastructure is concerned - you'd rather configure something that exists than write something new - paired with a bias toward shipping when it comes to solutions. Clear communication. You can explain a trade-off to a fund manager and hold your own in a technical review with a central engineering team. Comfort with real ownership in a small team, where you set the working patterns rather than inherit them. Full-stack or application development experience, particularly with Streamlit, FastAPI or HTMX. Familiarity with the Databricks ecosystem - Unity Catalog, Databricks Apps, Lakebase, Genie - or equivalent tooling. Experience with vector search, embeddings, document AI or retrieval-augmented generation in production. Experience with Terraform, GitHub Actions or similar, to keep configuration version-controlled and repeatable. FinOps experience: usage monitoring, budgets, showback and chargeback. Having supported analysts and non-specialist builders using a shared data environment. Experience in a regulated or audited setting such as financial services, infrastructure investment or energy. Familiarity with renewable energy, infrastructure investment or financial services data. As an equal opportunity employer, we do not discriminate on the basis of any protected attribute. Our commitment is to provide equal opportunities, an inclusive work environment, and fairness for everyone. If you'd like to know more about how we use your data, you can reach out to us via email at . We're happy to help! #J-18808-Ljbffr

Help us make a big green dent in the universe. We're on a mission to drive the global renewable energy revolution, and we need many more people to help us make our vision a reality. Octopus Energy Generation (OEGEN) is a leader in sourcing, investing in, and managing a wide range of utility-scale renewable energy assets. As we continue to expand our investment base, we are dedicated to building a diverse team that reflects the communities we serve. Currently, we manage a global portfolio of over £8 billion in renewable energy assets. We are committed to delivering best-in-class responsible investment activity, offering like-minded investors the means and products to invest their capital sustainably. It is our ambition to change the entire energy lifecycle and make every green electron matter, delivering the best outcomes for customers, investors, the environment and society, accelerating the transition to net zero. We are embarking on a comprehensive transformation program designed to drive significant advancements in our business operations and technology landscape. Our primary goal is to transition from our current reliance on legacy systems and specialized off-the-shelf tools to a more integrated, AI-driven, and data-centric operational model. Leveraging insights and guidance from our other technically mature entities like Kraken and OE, we plan to adopt cutting-edge tools and capabilities, particularly in AI and Python-driven solutions. By investing in a diverse range of skills, we aim to create a hybrid team capable of operating in both our legacy and future environments, ultimately transforming OEGEN into an efficient, data-driven organization. The tools are already here. Like the rest of OE Group, OEGEN runs on Databricks, we're moving onto our own Microsoft 365 tenant, and Octopus Energy Group gives us access to a powerful set of shared data and AI capabilities. What we're missing is someone whose job is to make all of it work together for our Fund Management business - and then build genuinely useful things on top of it. This is a two-sided role. On one side, you'll integrate: wiring third-party systems, internal apps and document storage into the environment we already have, setting sensible guardrails around access and cost, and adopting existing Group capability wherever it does the job rather than rebuilding it. On the other, you'll build: turning those connections into data products, internal tools and AI-enabled workflows that fund management, asset management and finance use every day. Tying the two together, you'll develop and own the playbook - the documented, repeatable patterns for how a new system gets connected, how a tool gets built and shipped, and how both get supported afterwards - so that what you learn once becomes how the whole team works. The two halves feed each other: you'll understand what's possible because you built the plumbing, and you'll build better plumbing because you know what people actually do with it. Integrate the systems our business runs on - third-party providers, internal tools, our own SharePoint and Microsoft 365 tenant - into our existing Databricks environment, via APIs and existing connectors. Build data products on top of what you connect: well-modelled, documented, reusable datasets that the business consumes directly through Excel, dashboards and natural-language querying, rather than one-off extracts. Design and ship internal applications and AI-enabled tools - using Python, Streamlit, Databricks Apps (HTMX), Lakebase, FastAPI or similar - that put data and AI directly into the hands of fund management, asset management and finance teams. Prototype, evaluate and productionise new AI capability, from document AI and retrieval to agentic workflows, and turn the ideas that prove out into supported products rather than abandoned experiments. Take an adopt-first approach: work with Octopus Energy Group's data platform and AI teams to reuse capability that already exists, and configure it for OEGEN rather than building parallel versions of it. Set up practical guardrails inside Databricks and Unity Catalog - schema and workspace access, permissions, environment hygiene - so more teams can use it without stepping on each other. Bring cost management from reactive to proactive: tagging, budgets, alerting and usage monitoring, so Databricks and AI token spend can be attributed to the right team, project or fund before the invoice arrives. Get our AI usage properly credentialed and logged - managed keys and access rather than API keys sitting in individual password managers - and provide clean patterns for embedding AI into the tools we build. Standardise how we build and ship internal apps: shared templates, authentication, deployment and documentation, so a tool remains supportable by someone other than the person who wrote it. Consolidate the ad-hoc scripts, spreadsheets and no-code workflows we've accumulated into fewer, better-understood integrations that don't need babysitting, and automate the repetitive parts of our own workflow. Work directly with non-technical teams to understand their problems and translate them into things we can build. Strong systems integration experience - connecting business systems, SaaS tools and data sources via REST APIs, connectors and authentication flows. A track record of building and shipping data products or internal applications that people actually use, not just pipelines that feed someone else's reports. Solid Python and SQL, used daily for building, automation and data modelling. Hands-on experience with a cloud data platform in production (Databricks preferred): workspaces, catalogs, permissions and compute. Practical experience integrating AI into real tools - LLM APIs, retrieval, agents - with a clear-eyed sense of what works and what's still a demo. Practical identity and access experience - SSO, service accounts, credential management and access lifecycle - enough to make sensible, secure choices without a security team holding your hand. Experience with Microsoft 365 / SharePoint integration, or a comparable enterprise document and collaboration stack. Real experience keeping cloud or AI usage costs under control: you know what drives the bill and how to attribute and cap it. A pragmatist's instinct for adopting over building where infrastructure is concerned - you'd rather configure something that exists than write something new - paired with a bias toward shipping when it comes to solutions. Clear communication. You can explain a trade-off to a fund manager and hold your own in a technical review with a central engineering team. Comfort with real ownership in a small team, where you set the working patterns rather than inherit them. Full-stack or application development experience, particularly with Streamlit, FastAPI or HTMX. Familiarity with the Databricks ecosystem - Unity Catalog, Databricks Apps, Lakebase, Genie - or equivalent tooling. Experience with vector search, embeddings, document AI or retrieval-augmented generation in production. Experience with Terraform, GitHub Actions or similar, to keep configuration version-controlled and repeatable. FinOps experience: usage monitoring, budgets, showback and chargeback. Having supported analysts and non-specialist builders using a shared data environment. Experience in a regulated or audited setting such as financial services, infrastructure investment or energy. Familiarity with renewable energy, infrastructure investment or financial services data. As an equal opportunity employer, we do not discriminate on the basis of any protected attribute. Our commitment is to provide equal opportunities, an inclusive work environment, and fairness for everyone. If you'd like to know more about how we use your data, you can reach out to us via email at . We're happy to help! #J-18808-Ljbffr

BLP Digital is redefining ERP automation with agentic AI. Spun out of ETH Zurich and HSG, we build AI agents that automate finance, procurement, logistics, sales, and more for some of the world's largest enterprises. We solve real enterprise problems with cutting-edge technology and a strong sense of ownership. Our solution is live in 40+ countries, used by 550+ customers, and automates 70,000+ processes every day, including for Fortune 500 companies. As one of Switzerland's fastest-growing SaaS scaleups, our success stems from deep expertise in technology and business processes, delivering a product with outstanding product-market fit, proven by a growing global customer base. We've recently welcomed Goldman Sachs Alternatives as a growth investor, and we're now expanding into the UK with the launch of our London office. We are just getting started. Ready to build the future? Join BLP Digital today. We're giving you the keys to the machine. As our Applied AI Engineer, you'll have a founder-level mandate to build and ship AI-powered internal tools that make our hiring, finance and ops workflows 10x faster — not 10% faster. You'll work at the frontier of what's possible with LLMs, AI agents, and emerging AI tooling, and apply it where it matters most: inside our own company. Build and ship AI-powered internal tools fast — we're talking days and weeks, not quarters Evaluate, integrate, and chain the latest AI models, APIs, and frameworks (LLMs, agent frameworks, embedding pipelines, AI coding tools) into production-ready internal solutions Create compounding leverage — every tool you build should free up hours across the entire company Write clean, maintainable code that integrates with our existing systems — APIs, databases, third-party services — and doesn't break at scale Own your deployments end-to-end: build it, test it, ship it, monitor it — and build it well enough that it runs reliably without babysitting Technical background with real building experience — CS degree, bootcamp, self-taught, we don't care as long as you've shipped things that work You've built with modern AI tooling (LLMs, AI coding assistants, workflow automation) and you're obsessed with what's coming next Startup or entrepreneurial DNA — you've either founded something, built an internal tool that became critical infra, or hacked together solutions that people actually used You move fast, communicate clearly, and love collaborating with non-technical teams to understand their pain points and turn them into elegant, automated solutionsFluency in English, German is a plus Bonus: experience with tools like Make, n8n, Retool, Supabase, or similar — but honestly, we care more about your ability to learn any tool in a weekend Solve real problems, fast. Join a high-growth deep-tech startup tackling real-world challenges for global industry leaders. Build from zero to one. Take ownership of our internal tooling landscape — shaping its foundations and direction from the ground up. Opportunities to grow. You're controlling your personal development and career trajectory in a rapidly growing, internationally expanding startup Exceptional colleagues. You'll be growing alongside individuals from exceptional academic backgrounds and careers Find Jobs in United Kingdom on Arbeitnow #J-18808-Ljbffr

Architect the platform that runs home life. We're hiring a Lead Backend Engineer to design a global, agentic-first platform for moving and home life. Fast enough for live voice. Reliable enough for agents to act on their own. 4M+ home movers a year in the UK · 28M UK households to run · $1T+ global market for home services We are looking for a truly world-class engineer who has seen what great looks like and can take ownership to build the foundations for a global agentic marketplace. OpenClaw meets Amazon, for your home. Moving is the second most stressful thing most people do, and the admin never stops. Jay is the personal AI that takes it off your plate. It sets the household up: energy, broadband, water, council tax, insurance and so much more, then keeps it running. It tracks renewals, finds the next deal, and grows with the customer from first rental to first mortgage, with credit and higher-value financial products next. People get back their time, save money and their peace of mind. Underneath Jay is the platform you'd architect. One side plugs into the property industry: letting agents, CRMs like Alto, deposit schemes, partners like OpenRent and IKEA UK, and the systems that already know someone is moving. The other plugs into hundreds of suppliers across every category a home needs. In the middle, one entity model and one API turn a move into services set up, switched and paid for, Stripe-like. UK first, then the world. Nobody has rebuilt this industry for AI. The comparison sites and incumbents still run on forms and call queues. The backend is where that changes. The architecture. Households, properties, partners, suppliers and how they relate. State machines every order runs on, clear enough for an agent to act on. Contracts between domains, data, queues, infrastructure. You design it and you build it. Speed and reliability, designed in. Live voice needs sub-second reads and a platform that doesn't need babysitting. Latency budgets per domain, observability shipped with the feature, rollback rehearsed every release, small changes to production daily. You'll move live systems onto a modern stack without dropping anything. Agents as first-class customers. Permissioned access for Jay and partner agents to read and act, with idempotency, audit trails and a hard line around money. Config over code, so commercial teams change pricing without a deploy. How you work becomes how engineering works. Whatever stands between us and it is yours to clear. How we get there is written down, twelve principles in three parts: • Think: Customer obsessed · AI native · Thinks big · Mission before self, • Build: Master of craft · Bias for action · Delivers outcomes · Builds out loud, • Together: True ownership · Trustworthy · Seeks and gives feedback · Inspiring to work with, • You're a systems thinker first. How the parts interact, where failure hides, what breaks at ten times the volume., • You've architected real systems end to end, more than once, and run them in production at the scale of millions of users., • You take the edges seriously. Retries, idempotency, backpressure, the message that arrives twice., • You raise everyone around you. The standard goes up on work you never touch. You are great to work with and will make work more joyful., • You're AI-native at the frontier, and you set the practice for the team, from planning to evals., • You're strong in TypeScript, productive in whatever a problem needs within days, and happiest thinking out loud with the team., • You've led a team, or worked in UK property or utilities., • You've moved house in the UK and it made you angry. We want the specific story., • You already have ideas about how it should work. Bring them to the first call. We're a B Corp, so the values are real. We're FCA regulated, so doing things properly in a regulated industry is part of how we build. And we're obsessed with the customer, which is how we hold 4.9 on both Trustpilot and Google. TypeScript on the backend, Python and FastAPI for Jay, Next.js up front, AWS underneath, Claude Code woven through how we build. You won't have used all of it, and you'll change some of it. Location: London, a few days a week in the office Pay: Cash competitive, plus equity Hours: Work hard, play hard. Crunch time means late nights and weekends. In general, great work-life balance. Reports to: Head of AI and Engineering Right to work: UK right to work required #J-18808-Ljbffr

Architect the platform that runs home life. We're hiring a Lead Backend Engineer to design a global, agentic-first platform for moving and home life. Fast enough for live voice. Reliable enough for agents to act on their own. 4M+ home movers a year in the UK · 28M UK households to run · $1T+ global market for home services We are looking for a truly world-class engineer who has seen what great looks like and can take ownership to build the foundations for a global agentic marketplace. The opportunity: OpenClaw meets Amazon, for your home. Moving is the second most stressful thing most people do, and the admin never stops. Jay is the personal AI that takes it off your plate. It sets the household up: energy, broadband, water, council tax, insurance and so much more, then keeps it running. It tracks renewals, finds the next deal, and grows with the customer from first rental to first mortgage, with credit and higher-value financial products next. People get back their time, save money and their peace of mind. Underneath Jay is the platform you'd architect. One side plugs into the property industry: letting agents, CRMs like Alto, deposit schemes, partners like OpenRent and IKEA UK, and the systems that already know someone is moving. The other plugs into hundreds of suppliers across every category a home needs. In the middle, one entity model and one API turn a move into services set up, switched and paid for, Stripe-like. UK first, then the world. Nobody has rebuilt this industry for AI. The comparison sites and incumbents still run on forms and call queues. The backend is where that changes. What you'll own: three things, end to end. The architecture. Households, properties, partners, suppliers and how they relate. State machines every order runs on, clear enough for an agent to act on. Contracts between domains, data, queues, infrastructure. You design it and you build it. Speed and reliability, designed in. Live voice needs sub-second reads and a platform that doesn't need babysitting. Latency budgets per domain, observability shipped with the feature, rollback rehearsed every release, small changes to production daily. You'll move live systems onto a modern stack without dropping anything. Agents as first-class customers. Permissioned access for Jay and partner agents to read and act, with idempotency, audit trails and a hard line around money. Config over code, so commercial teams change pricing without a deploy. How you work becomes how engineering works. How we build: a lead owns the outcome. Whatever stands between us and it is yours to clear. How we get there is written down, twelve principles in three parts: Think: Customer obsessed · AI native · Thinks big · Mission before self Build: Master of craft · Bias for action · Delivers outcomes · Builds out loud Together: True ownership · Trustworthy · Seeks and gives feedback · Inspiring to work with Who thrives here: you should apply if You're a systems thinker first. How the parts interact, where failure hides, what breaks at ten times the volume. You've architected real systems end to end, more than once, and run them in production at the scale of millions of users. You take the edges seriously. Retries, idempotency, backpressure, the message that arrives twice. You raise everyone around you. The standard goes up on work you never touch. You are great to work with and will make work more joyful. You're AI-native at the frontier, and you set the practice for the team, from planning to evals. You're strong in TypeScript, productive in whatever a problem needs within days, and happiest thinking out loud with the team. Bonus points You've led a team, or worked in UK property or utilities. You've moved house in the UK and it made you angry. We want the specific story. You already have ideas about how it should work. Bring them to the first call. The team and the stack: who you'd build with. We're a B Corp, so the values are real. We're FCA regulated, so doing things properly in a regulated industry is part of how we build. And we're obsessed with the customer, which is how we hold 4.9 on both Trustpilot and Google. The stack: TypeScript on the backend, Python and FastAPI for Jay, Next.js up front, AWS underneath, Claude Code woven through how we build. You won't have used all of it, and you'll change some of it. The details Location: London, a few days a week in the office Pay: Cash competitive, plus equity Hours: Work hard, play hard. Crunch time means late nights and weekends. In general, great work-life balance. Reports to: Head of AI and Engineering Right to work: UK right to work required TPBN1_UKTJ

Help us make a big green dent in the universe. We're on a mission to drive the global renewable energy revolution, and we need many more people to help us make our vision a reality. Octopus Energy Generation (OEGEN) is a leader in sourcing, investing in, and managing a wide range of utility-scale renewable energy assets. As we continue to expand our investment base, we are dedicated to building a diverse team that reflects the communities we serve. Currently, we manage a global portfolio of over £8 billion in renewable energy assets. We are committed to delivering best-in-class responsible investment activity, offering like-minded investors the means and products to invest their capital sustainably. It is our ambition to change the entire energy lifecycle and make every green electron matter, delivering the best outcomes for customers, investors, the environment and society, accelerating the transition to net zero. We are embarking on a comprehensive transformation program designed to drive significant advancements in our business operations and technology landscape. Our primary goal is to transition from our current reliance on legacy systems and specialized off-the-shelf tools to a more integrated, AI-driven, and data-centric operational model. Leveraging insights and guidance from our other technically mature entities like Kraken and OE, we plan to adopt cutting-edge tools and capabilities, particularly in AI and Python-driven solutions. By investing in a diverse range of skills, we aim to create a hybrid team capable of operating in both our legacy and future environments, ultimately transforming OEGEN into an efficient, data-driven organization. The tools are already here. Like the rest of OE Group, OEGEN runs on Databricks, we're moving onto our own Microsoft 365 tenant, and Octopus Energy Group gives us access to a powerful set of shared data and AI capabilities. What we're missing is someone whose job is to make all of it work together for our Fund Management business - and then build genuinely useful things on top of it. This is a two-sided role. On one side, you'll integrate: wiring third-party systems, internal apps and document storage into the environment we already have, setting sensible guardrails around access and cost, and adopting existing Group capability wherever it does the job rather than rebuilding it. On the other, you'll build: turning those connections into data products, internal tools and AI-enabled workflows that fund management, asset management and finance use every day. Tying the two together, you'll develop and own the playbook - the documented, repeatable patterns for how a new system gets connected, how a tool gets built and shipped, and how both get supported afterwards - so that what you learn once becomes how the whole team works. The two halves feed each other: you'll understand what's possible because you built the plumbing, and you'll build better plumbing because you know what people actually do with it. We want someone with genuine ideas about where AI can take a business like ours, and the pragmatism to ship them. Our team has already built an Excel data mart plugin that puts gold-layer tables directly in the hands of non-technical staff, a metrics taxonomy app that keeps third-party definitions aligned with our own, and AI-assisted workflows that scaffold documentation automatically. There's a long list of things we haven't got to yet. Expect roughly half your time on integration and enablement and half on building, and expect to work closely with the central data platform team so what we do in OEGEN stays consistent with the wider estate and our specific needs get onto their roadmap. • Integrate the systems our business runs on - third-party providers, internal tools, our own SharePoint and Microsoft 365 tenant - into our existing Databricks environment, via APIs and existing connectors., • Build data products on top of what you connect: well‑modelled, documented, reusable datasets that the business consumes directly through Excel, dashboards and natural‑language querying, rather than one‑off extracts., • Design and ship internal applications and AI‑enabled tools - using Python, Streamlit, Databricks Apps (HTMX), Lakebase, FastAPI or similar - that put data and AI directly into the hands of fund management, asset management and finance teams., • Prototype, evaluate and productionise new AI capability, from document AI and retrieval to agentic workflows, and turn the ideas that prove out into supported products rather than abandoned experiments., • Take an adopt‑first approach: work with Octopus Energy Group's data platform and AI teams to reuse capability that already exists, and configure it for OEGEN rather than building parallel versions of it., • Set up practical guardrails inside Databricks and Unity Catalog - schema and workspace access, permissions, environment hygiene - so more teams can use it without stepping on each other., • Bring cost management from reactive to proactive: tagging, budgets, alerting and usage monitoring, so Databricks and AI token spend can be attributed to the right team, project or fund before the invoice arrives., • Get our AI usage properly credentialed and logged - managed keys and access rather than API keys sitting in individual password managers - and provide clean patterns for embedding AI into the tools we build., • Standardise how we build and ship internal apps: shared templates, authentication, deployment and documentation, so a tool remains supportable by someone other than the person who wrote it., • Consolidate the ad‑hoc scripts, spreadsheets and no‑code workflows we've accumulated into fewer, better‑understood integrations that don't need babysitting, and automate the repetitive parts of our own workflow., • Work directly with non‑technical teams to understand their problems and translate them into things we can build., • Strong systems integration experience - connecting business systems, SaaS tools and data sources via REST APIs, connectors and authentication flows., • A track record of building and shipping data products or internal applications that people actually use, not just pipelines that feed someone else's reports., • Solid Python and SQL, used daily for building, automation and data modelling., • Hands‑on experience with a cloud data platform in production (Databricks preferred): workspaces, catalogs, permissions and compute., • Practical experience integrating AI into real tools - LLM APIs, retrieval, agents - with a clear‑eyed sense of what works and what's still a demo., • Practical identity and access experience - SSO, service accounts, credential management and access lifecycle - enough to make sensible, secure choices without a security team holding your hand., • Experience with Microsoft 365 / SharePoint integration, or a comparable enterprise document and collaboration stack., • Real experience keeping cloud or AI usage costs under control: you know what drives the bill and how to attribute and cap it., • A pragmatist's instinct for adopting over building where infrastructure is concerned - you'd rather configure something that exists than write something new - paired with a bias toward shipping when it comes to solutions., • Clear communication. You can explain a trade‑off to a fund manager and hold your own in a technical review with a central engineering team., • Comfort with real ownership in a small team, where you set the working patterns rather than inherit them., • Full‑stack or application development experience, particularly with Streamlit, FastAPI or HTMX., • Familiarity with the Databricks ecosystem - Unity Catalog, Databricks Apps, Lakebase, Genie - or equivalent tooling., • Experience with vector search, embeddings, document AI or retrieval‑augmented generation in production., • Experience with Terraform, GitHub Actions or similar, to keep configuration version‑controlled and repeatable., • FinOps experience: usage monitoring, budgets, showback and chargeback., • Having supported analysts and non‑specialist builders using a shared data environment., • Experience in a regulated or audited setting such as financial services, infrastructure investment or energy., • Familiarity with renewable energy, infrastructure investment or financial services data. Octopus Energy Group is a unique culture. An organisation where people learn, decide, and build quicker. Where people work with autonomy, alongside a wide range of amazing co‑owners, on projects that break new ground. We want your hard work to be rewarded with perks you actually care about! We were recently named the UK's top company to work for, and we ranked in the top ten in the Sunday Times Best Places to Work 2024. Our Group CEO, Greg has recorded a podcast about our culture and how we empower our people. We've also been placed in the top 10 companies for senior leadership. As an equal opportunity employer, we do not discriminate on the basis of any protected attribute. Our commitment is to provide equal opportunities, an inclusive work environment, and fairness for everyone. #J-18808-Ljbffr

at Resilia || Remote - Worldwide Resilia is hiring 1–2 senior Meta Media Buyers to take full, hands‑on ownership of our Meta ad account. You are the pilot, and there is no co‑pilot double‑checking your work. You will own Resilia's Meta account end‑to‑end across Facebook and Instagram: structure, launches, budgets, scaling, and daily performance. We are looking for operators who have already run accounts at serious scale and can make high‑stakes calls independently, quickly, and correctly. If you need sign‑off on every budget change or someone reviewing each launch, this is not the role. If you want real budget, real authority, and real accountability, it is. • Full Account Ownership: Own the Meta account end‑to‑end, including structure, campaigns, budgets, and results, with no babysitting and no one re‑checking your day‑to‑day decisions., • Budget Scaling at Volume: Run and scale high six‑figure daily ad spend, managing pacing and allocation to hit CAC, MER, and margin targets., • Launch Velocity: Launch new ads and creative variations quickly and cleanly, with naming conventions, QA, and tracking right the first time, so testing never bottlenecks on execution., • Multi‑SKU Structure: Manage multiple SKUs within one ad account under a clear, scalable structure, so spend allocation, learnings, and performance by product stay readable at all times., • Volatility Management: Diagnose and respond to performance swings in real time, including intra‑day budget adjustments, separating noise from genuine decline, and knowing when to cut, hold, or push., • Testing Frameworks: Build and run structured tests across creatives, angles, offers, and audiences, and turn results into scaling decisions., • Creative Feedback: Translate account data into clear, actionable creative direction for the production team., • Reporting: Report performance against business KPIs, not just platform‑reported numbers, with a clear point of view on what to do next., • Proven Track Record at Scale: You have personally managed high 7‑ to 8‑figure total Meta ad spend., • High Daily Spend Experience: Hands‑on experience running and managing high six‑figure daily ad spend, and comfort making decisions where every hour carries real money., • 3–6+ Years Experience: Hands‑on ownership of high‑spend Meta accounts in DTC/e‑commerce., • Advanced KPI Fluency: Strategic command of metrics well beyond native Meta reporting: MER/blended ROAS, new‑customer CAC, contribution margin, LTV:CAC, payback period, marginal vs. average CPA, and incrementality. You know when platform numbers are misleading and what to trust instead., • Meta Performance Intuition: Deep understanding of how Meta delivery behaves, including learning phases, the effect of budget changes, CPM fluctuations, and intra‑day and day‑of‑week patterns, and how to manage volatility without overreacting., • Multi‑SKU Account Experience: You have run accounts with multiple products or SKUs without losing structure, clarity, and control of spend allocation., • Flawless Execution: A track record of launching high volumes of ads and creative variations seamlessly and without costly errors., • Platform Fluency: Deep knowledge of Advantage+, CBO/ABO, cost caps, bid caps, and manual bidding., • Attribution Knowledge: Familiarity with Triple Whale, Northbeam, or similar tools, and comfort reconciling platform, third‑party, and backend data., • Complete Autonomy: You work fully independently. You make the call, own the outcome, and communicate proactively, without needing supervision or approval on routine decisions. We prioritize output over hours. However, because this role owns live budgets at high daily spend, we require strong overlap with US business hours (EST/PST) for real‑time scaling, intra‑day adjustments, and troubleshooting. Resilia is a fast‑growing consumer packaged goods (CPG) and supplement brand dedicated to moving past generic health trends and delivering premium, highly credible wellness solutions. We blend cutting‑edge formulation with authentic education to empower consumers to take control of their full‑body health. Resilia is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We consider all qualified applicants for employment regardless of race, religious creed, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex, gender, gender identity, gender expression, pregnancy, childbirth and breastfeeding, age, sexual orientation, military or veteran status, or any other protected classification, in accordance with applicable federal, state, and local laws. If you have a disability or special need that requires accommodation, please feel free to contact us. #J-18808-Ljbffr

Join BLP Digital - The #1 Solution for ERP Automation BLP Digital is redefining ERP automation with agentic AI. Spun out of ETH Zurich and HSG, we build AI agents that automate finance, procurement, logistics, sales, and more for some of the world's largest enterprises. We solve real enterprise problems with cutting-edge technology and a strong sense of ownership. Our solution is live in 40+ countries, used by 550+ customers, and automates 70,000+ processes every day, including for Fortune 500 companies. As one of Switzerland's fastest-growing SaaS scale-ups, our success stems from deep expertise in technology and business processes, delivering a product with outstanding product-market fit, proven by a growing global customer base. We've recently welcomed Goldman Sachs Alternatives as a growth investor, and we're now expanding into the UK and USA. We are just getting started. Ready to build the future? Join BLP Digital today. We're giving you the keys to the machine. As our Applied AI Engineer, you'll have a founder-level mandate to build and ship AI-powered internal tools that make our hiring, finance and ops workflows 10x faster, not 10% faster. You'll work at the frontier of what's possible with LLMs, AI agents, and emerging AI tooling, and apply it where it matters most: inside our own company. Build and ship AI-powered internal tools fast: we're talking days and weeks, not quarters Evaluate, integrate, and chain the latest AI models, APIs, and frameworks (LLMs, agent frameworks, embedding pipelines, AI coding tools) into production-ready internal solutions Create compounding leverage: document and share each tool well enough that it frees up hours company-wide, not just for you Write clean, maintainable code that integrates with our existing systems (APIs, databases, third-party services) and doesn't break at scale Own your deployments end-to-end: build it, test it, ship it, monitor it, and build it well enough that it runs reliably without babysitting Technical background with real building experience: CS degree, bootcamp, self-taught, we don't care as long as you've shipped things that work You've built with modern AI tooling (LLMs, AI coding assistants, workflow automation) and you're obsessed with what's coming next Startup or entrepreneurial DNA: you've either founded something, built an internal tool that became critical infra, or hacked together solutions that people actually used You move fast, communicate clearly, and love collaborating with non-technical teams to understand their pain points and turn them into elegant, automated solutions Fluency in English, German is a plus Bonus: experience with tools like Make, n8n, Retool, Supabase, or similar, but honestly, we care more about your ability to learn any tool in a weekend Build from zero to one. Take ownership of our internal tooling landscape, shaping its foundations and direction from the ground up. A founder-level mandate. You decide what gets built and how, with direct access to the latest LLMs, agent frameworks, and AI coding tools. Speed as the standard. Ship in days and weeks, not quarters, and see your tools change how the company runs within the same month. Learn more about blp and our values at blp.digital/company/careers. #J-18808-Ljbffr

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