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AI Engineer (PhD) – Series A Deep Tech AI Company About the Company: Our client is a cutting-edge deep tech start-up that’s redefining how enterprises leverage artificial intelligence to automate complex analytical workflows. Having completed a successful Series A funding round, they are rapidly scaling their technology and delivery teams to meet strong enterprise demand. Their mission is to replace traditional, fragmented analytics processes with intelligent AI-powered digital workers — autonomous systems that can perform advanced analytics, data science, and decision-making tasks continuously, accurately, and at scale. The Role: As an AI Engineer, you’ll be part of a world-class team building and deploying production-grade AI systems that redefine enterprise analytics. This is a high-impact, client-facing position where you’ll design, implement, and deliver agentic workflows and intelligent systems that solve real business challenges at scale. You’ll collaborate with senior stakeholders, data scientists, and product teams at some of the world’s most recognized enterprises — translating complex business problems into elegant, scalable AI solutions. What You’ll Do: • Lead the design and delivery of agentic AI systems and LLM-based workflows for top-tier enterprise clients., • Partner directly with technical and business teams to identify pain points and architect high-impact AI-driven solutions., • Build and deploy production-grade systems leveraging LLMs, RAG pipelines, multi-component AI programs (MCPs), and agent frameworks., • Conduct applied research to solve novel, previously unseen problems — bringing cutting-edge innovation from concept to production., • Contribute to internal research initiatives and thought leadership, shaping the evolution of AI automation in enterprise contexts. What You’ll Bring: • PhD in a STEM field (Computer Science, Machine Learning, Mathematics, Physics, or related discipline). Your research background enables you to tackle complex, ambiguous problems with scientific rigor and creativity., • Proven hands-on experience building and deploying LLM-based or agentic systems in production environments., • Strong understanding of RAGs, MCPs, and scalable AI architectures., • A forward-deployed engineering mindset — comfortable engaging directly with clients to understand business needs and deliver measurable results., • Excellent communication and problem-solving skills, with the ability to translate between technical and commercial perspectives. Why Join: • Be part of a fast-growing Series A company that’s transforming how enterprises use AI., • Work on real-world, high-impact AI projects with globally recognized clients., • Collaborate with some of the brightest minds in AI and applied research., • Join a culture that prizes curiosity, ownership, and performance — where winning as a team is the ultimate goal.

Infrastructure AI Engineer – Series A Deep Tech AI Company About the Company: Our client is a pioneering deep tech company transforming how enterprises leverage artificial intelligence to automate complex analytics workflows. Following a successful Series A funding round, the company is scaling rapidly to meet growing demand from some of the world’s largest organizations. Their platform delivers AI-powered digital workers — autonomous systems that perform sophisticated analytics and data science tasks continuously and intelligently. By replacing fragmented tools, manual consulting, and costly licenses, these digital workers enable enterprises to achieve insights 10x faster and at a fraction of the cost, with guaranteed outcomes and zero operational overhead. The Role: As an Infrastructure AI Engineer, you’ll design, deploy, and manage the infrastructure that powers some of the most advanced AI systems in production today. You’ll work at the intersection of cloud computing, AI operations, and DevOps, ensuring scalable, secure, and high-performing environments for enterprise AI deployments. This is a hands-on, client-facing role where you’ll collaborate with technical and business teams to bring cutting-edge AI agents and workflows to life across multi-cloud and on-premise environments. What You’ll Do • Architect, deploy, and maintain production-grade AI solutions across multi-cloud and on-prem infrastructures., • Design and manage Kubernetes-based environments to support high-performance AI workloads., • Implement best practices for availability, observability, scalability, and security in AI infrastructure., • Collaborate with enterprise clients to understand deployment constraints and design tailored solutions., • Integrate and operationalize LLMs, RAGs, MCPs, and agentic AI workflows into robust environments., • Build and optimize CI/CD pipelines and infrastructure-as-code (IaC) frameworks (e.g., Terraform, Helm)., • Partner closely with AI engineering teams to ensure smooth delivery from prototype to production. What You’ll Bring • Strong background in cloud infrastructure engineering — experience with at least one major provider (AWS, Azure, or GCP)., • Proven ability to deploy and manage systems across hybrid or multi-cloud and on-premise environments., • Expertise with Kubernetes, Docker, and container orchestration at scale., • Familiarity with DevOps and site reliability engineering (SRE) best practices., • Experience with CI/CD automation and infrastructure-as-code tools., • Understanding of AI/ML deployment patterns and how to support model-driven workloads in production., • Strong client-facing communication and problem-solving skills, with a forward-deployed engineering mindset. Why Join • Join a fast-growing Series A company at the forefront of AI infrastructure innovation., • Work on cutting-edge, real-world AI deployments for top global enterprises., • Collaborate with world-class engineers and AI practitioners in a high-performance culture., • Be part of a team that values ownership, excellence, and impact — where winning together is the goal.