Senior Software Engineer

About the role  As a Senior Software Engineer, you deliver production work — including legacy modernisation — through agentic workflows, inside the teams setting the operating model for the rest of TOPdesk engineering.  The work is real and customer-facing: you'll build and modernise TOPdesk's Knowledge Base — expanding existing components, shipping new features, and improving the underlying technologies — for a service management platform used by millions of people every day. Some days that's an accessible, polished user interface; other days it's making the backend fast and reliable; often it's both across the stack.  You work with Claude Code as your primary collaborator: framing problems, orchestrating agents to build and modernise real product, and standing behind the verification. Working this way is the heart of the role, not an add-on.  What this is not: A traditional senior engineering role with optional AI tooling bolted on top. Building agentically is how the work gets done here.  The team  You join team Phoenix, one of the first teams adopting our AI-native SDLC, reporting to an Engineering Manager, proving it in production on real customer-facing systems. Phoenix is a cross-functional team spanning back-end, front-end, UX, testing, and product — you deliver alongside a UX designer and a Product Manager, and work with platform teams to get code to production.  Owns and evolves the Knowledge Base end to end, from UI to backend.  Ships legacy-modernisation and product work through agentic workflows.  Builds the shared prompt and agent libraries the wider org adopts.  What you'll do  Build agentically  Frame and decompose problems, orchestrate agents to implement them, and verify the result.  Build new agentic product capabilities, and modernise pieces of the legacy Java/MS SQL platform on the modern TS/Vue/Azure stack.  Work with agents, stay accountable  Write implementation briefs and acceptance criteria before invoking agents.  Curate context aggressively — the right files, constraints, and invariants; lean on CLAUDE.md conventions, subagents, and MCP tools to scale beyond single-shot prompting.  Design verification before or alongside implementation: tests, runtime checks, migration validation, observability, and rollback planning — plus the evals that catch regressions automatically.  Handle agent permissions, context, secrets, and dependency changes with care, and keep agent-generated change sets small, understandable, and maintainable with reviewable evidence behind them.  Recognise when a plausible agent-generated solution is architecturally wrong, unsafe, or unnecessarily complex — and review agent-generated work before it merges. You own the outcome.  Raise the bar  Contribute reusable patterns, subagents, and evals to the shared libraries the wider org adopts.  Pair with colleagues…