Engineering Manager

About the role 

As an Engineering Manager, you lead one or two teams with a specific technical mission — front-end, middleware, back-end, data, or platform — giving both people and technical direction, and owning what your teams ship.

You set team-level technical direction within the wider architectural guardrails, grow strong engineers into stronger ones, and own delivery and operational outcomes — creating the conditions for your senior and staff engineers to provide technical leadership too. You operate agents yourself and lead our AI-native SDLC from the front. You report to your domain's senior engineering leader.

What this is not  A purely process or Scrum-master role, or a hands-off manager who sets no technical direction. You lead people and technology together, and stay technically close through design, pairing, incident response, reviews, technical investigation, and agent workflows — regular individual coding output is not the measure of the role.

The team 

You lead one or two teams with a specific mission — for example front-end feature development, middleware, back-end services, data, or platform.

• Delivers its part of the domain's roadmap.
• Sets and upholds the technical standards for its domain.
• Adopts the target architecture and our AI-native SDLC practices.
• Sits within a approx 170-strong engineering organisation across Delft, Budapest, and Kaiserslautern.

What you'll do 

Provide technical direction

• Set technical direction and standards for your teams' domain, alongside your engineers.
• Make and steward the key technical decisions; uphold quality, security, and operational stability.
• Contribute to system and architecture decisions for your domain with the Enterprise Architects and your peers.

Grow the people

• Coach and develop your engineers — including growing strong ones into senior and staff engineers.
• Hire, and act on tough talent calls with clarity and care.

Own the delivery and the bar

• Own your teams' roadmap commitments and delivery and operational outcomes; protect cycle time, quality, and operational stability.
• Keep review sustainable in an agentic SDLC — ensure your teams do not create excessive review burden or unnecessary code, match agent autonomy to the risk of the task, and keep human accountability clear.
• Raise the engineering bar for your domain; make standards explicit and inspectable.
• Operate agents yourself — build the subagents, evals, and patterns your team reuses, and contribute them back to the shared libraries.

Technical environment 

Claude Code is our current primary agentic engineering environment: agents may plan and execute within defined constraints and governed environments, while engineers stay accountable for problem framing, architecture, acceptance criteria, security, verification, and production outcomes. Agent-generated work is backed by automated tests, runtime checks, reviewable evidence, and risk-based human approval — we match deterministic automation, structured workflows, or agents to the nature and risk of the task rather than maximising autonomy for its own sake.

• Your domain: front-end, middleware, back-end, data, or platform — the specific stack depends on your teams' mission.
• Legacy: Java, MS SQL, heritage architecture — being decomposed.
• Modern: Python, TypeScript, Vue, Postgres, Azure, Kubernetes; cloud-native / service-oriented architecture; Terraform-managed infrastructure.
• Mechanisms: subagents, MCP tool integrations, multi-agent workflows, and shared prompt, agent, and eval libraries.

Success in your first year 

• Your teams reliably deliver their part of the domain's roadmap, with measurably better cycle time, quality, and stability.
• Technical direction and standards for your domain are clear, owned, and upheld — the bar has gone up.
• Your engineers have grown, including movement into senior or staff roles.
• AI-native ways of working are normal in your team, with patterns and evals you contributed.

Required 

• Engineering manager with a track record of growing engineers — including into senior and staff roles — and owning team delivery.
• A strong technical foundation in a relevant domain (front-end, middleware, back-end, data, or platform) — you set team-level technical direction, not just run process.
• Current, personal practice of AI-native software delivery (Claude Code or equivalent) — you can show your work and lead by example.
• Strong on talent development; comfortable acting on tough calls.
• Comfortable in ambiguity and inside legacy codebases; a strong communicator.

Nice to have 

• Led a team through a significant technical or operating-model change.
• Has built and shared subagents, evals, or CLAUDE.md conventions a team reused.
• Deep domain expertise relevant to one of the product domains.

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