[Hiring] Engineering Manager - AI Product @Pragmatike

Role Description

Our client is a European technology company operating a cloud and infrastructure platform, and we are looking for an AI Engineering Manager to lead the small, high-leverage team behind their AI product. This team owns the full stack that makes the product work from model serving and inference infrastructure to the AI platform and application layer that users interact with.

You will combine leadership and technical depth, leading a team of 3 engineers, setting direction, and staying hands-on with production-grade code (~50%). With a team this size, your own output matters as much as your judgment: this is a player-coach role for a technical leader who can make strategic decisions, guide architecture, and ship reliable, cost-efficient AI systems at scale.

What You'll Do

• Lead, mentor, and grow a small, high-performing team of engineers focused on AI platform and product engineering
• Drive architectural direction for the AI product with an emphasis on inference performance, reliability, cost efficiency, and developer experience
• Contribute hands-on to design, implementation, and optimization of core AI systems (model serving, inference pipelines, retrieval, orchestration, evaluation)
• Own the AI/ML platform end to end: GPU capacity and scheduling, model deployment and versioning, data and embedding pipelines, monitoring and quality evaluation
• Collaborate closely with Product, Infrastructure, Security, and Backend teams to define priorities and ensure smooth integrations
• Conduct regular 1:1s, performance reviews, and technical coaching
• Foster a culture of ownership, engineering excellence, and continuous improvement
• Translate strategic objectives into actionable execution plans and ensure timely delivery
• Influence the evolution of the AI platform with pragmatic, forward-looking technical decisions
• Champion best practices across software development, automation, evaluation, and operational excellence

Qualifications

• 7+ years of experience in software engineering, including 2+ years in a technical leadership or engineering management role
• Proven experience building and operating AI/ML platform or inference infrastructure in production (model serving, GPU workloads, latency and cost optimization)
• Solid experience building distributed backend systems, strong Python, plus a systems language (Go, Rust, or similar) is a plus
• Hands-on familiarity with the modern LLM stack: model APIs and open-weight models, serving frameworks (vLLM, TGI, Triton or similar), retrieval/vector databases, and prompt or context engineering
• Strong grasp of AI product quality: evaluation frameworks, benchmarking, regression testing, and observability for non-deterministic systems
• Strong expertise in cloud platforms (AWS preferred: EC2, ECS, Lambda, IAM, CloudWatch) and GPU compute
• Familiarity with Kubernetes, containerization, and Infrastructure-as-Code (Terraform, Pulumi, AWS CDK)
• Understanding of CI/CD automation (GitHub Actions, CircleCI, or similar)
• Strong knowledge of Linux systems, networking fundamentals, and monitoring/alerting best practices
• Excellent communication and leadership skills, able to guide performance, set expectations, and motivate engineers
• Strong technical judgment and the ability to balance hands-on coding with people and strategic responsibilities

Benefits

• Own a product, not a component: Lead the team behind the company's AI product and shape the capabilities the wider business builds on
• High leverage, small team: With three engineers, your technical and strategic decisions translate directly into what ships
• Grow as a leader: Manage, mentor, and inspire a talented team while influencing strategic technical decisions
• Stay hands-on: Balance leadership with coding in a modern, high-scale AI platform environment
• Work with cutting-edge technology: Deepen your expertise in LLMs, inference infrastructure, GPU compute, and distributed systems at scale
• Drive platform evolution: Directly impact architecture, reliability, and AI quality across the organization
• Collaborate across teams: Work closely with Product, Infrastructure, Security, and Backend teams, expanding your cross-functional expertise
• Remote-first flexibility: Enjoy a fully remote role while aligning with the European time zone