Head Of Engineering Tech · Murphy HQ ·
2 days ago
Barcelona
Murphy AI is a next-generation debt collection platform powered by artificial intelligence , designed to optimize recovery rates while maintaining respectful and personalized communication. Our advanced automation streamlines the process of collecting overdue invoices for businesses, providing a seamless and effective solution . At Murphy AI, we’re tackling one of the toughest challenges in fintech: making debt recovery more efficient, autonomous and scalable. Our AI-powered agents adapt instantly, engaging with debtors across channels like voice, email and sms to maximize results while preserving trust. By combining advanced artificial intelligence with powerful automation, we’re setting a new standard for how businesses recover payments . As a fast-growing startup that has already made an impact within less than a year in the market, we are building a talented team to scale our operations and drive our vision forward As Head of Engineering at Murphy, your mission is to build and lead a high-performing engineering organization that delivers Murphy’s product and platform roadmap at startup speed while raising the bar on scalability, quality, security, and operational excellence in a regulated (banking) environment. You will own the engineering organization end-to-end: org design, leadership development, hiring, delivery performance, and platform maturity. You will establish a delivery operating system that makes execution predictable across squads, and you will drive a prioritized Tech Backlog Portfolio spanning AI platform foundations (agents/runtime performance, latency/cost discipline), QA and test automation, infrastructure/reliability and observability, and developer experience. You will partner closely with the CTO on technical strategy and architectural direction, and work deeply with Product and AI to shape scope, sequencing, and outcomes. As we scale from ~15 to 40+ engineers across multiple squads, you will provide multidisciplinary leadership across distributed architectures, infra/reliability, and AI systems, translating bank-grade expectations into pragmatic engineering controls and evidence without stalling product delivery—while building a culture of ownership, feedback, and engineering excellence. * Lead, grow, and coach an engineering organization scaling from ~15 to 40+ engineers across multiple squads; develop engineering managers and tech leads. * Define org design, team topology, and service ownership boundaries; ensure clear accountability and effective cross-squad collaboration. * Establish and run a delivery operating system that drives predictable outcomes (planning cadence, scope discipline, definition of done, release rhythm). * Own execution of product and platform roadmaps; manage dependencies, risks, and tradeoffs to deliver high-quality outcomes on time. * Drive a prioritized Tech Backlog Portfolio across AI platform, QA/test automation, infrastructure/reliability and observability, and developer experience, with clear owners and measurable impact. * Partner with the CTO on technical strategy and architectural direction in a microservices, event-driven environment; mature the platform without disrupting delivery. * Partner with Product to shape scope, sequencing, and measurable outcomes; translate business priorities into executable plans and resourcing. * Raise engineering quality and operational excellence (testing strategy, CI reliability, release confidence, incident response, observability, on-call health). * Embed security-by-default and compliance-by-design practices suitable for regulated customers (banks): auditability, access controls, data handling, SDLC controls, change management, incident readiness. * 5+ years in software engineering roles, including 8+ years in engineering leadership (EM/Head/Director level), ideally in fast-growing startups/scale-ups. * Proven experience scaling and leading high-performing engineering teams through multi-squad growth (e.g., scaling an org from ~10 to 50+ engineers, or equivalent complexity). * Track record managing managers and/or multiple teams, including org design, hiring, performance management, and leadership development. * Strong technical judgment across backend architecture and distributed systems; experience operating microservices and event-driven systems (Kafka or equivalent). * Credible depth across infrastructure/reliability (observability, incident management, CI/CD) and engineering quality practices (testing, release engineering). * Experience building or operating AI-enabled products (LLMs/agents) with real tradeoffs (latency, cost, evaluation/quality, reliability). * Demonstrated ability to implement a delivery operating system that improves predictability and throughput without sacrificing quality. * Experience operating in security-sensitive or regulated contexts; capable of translating requirements into pragmatic controls and evidence. * Excellent communication and stakeholder management; can align Engineering, Product, and AI and translate technical work into business impact. * Comfortable working in a hybrid environment and leading distributed collaboration effectively.