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Staff Engineer Agentic AI

Believe

Skills

Required

  • workflows
  • observability
  • software engineering
  • LLM-based
  • coding
  • API design
  • concurrency
  • data modelling
  • CI/CD
  • containerised deployment
  • structured outputs
  • multi-step planning
  • state
  • LLM-as-judge

Join Believe, a fast-growing company in the music industry, as a Staff Engineer in Core Engineering. In this hands-on, deeply technical role, you will design and build systems for intelligent automation and large-scale retrieval. You will work alongside the Agentic & Automation team and have a significant impact on the company's success.

Construire notre cadre d'agentic d'entreprise : orchestration, récupération et collaboration entre plusieurs agents.

Responsibilities

  • Écrire du code de production : bien structuré, efficace et testable, à travers les services de production.
  • Rendre les systèmes d'IA mesurables et fiables : ensembles de données dorées, évaluations hors ligne et en ligne.

Requirements

  • 5+ years in software engineering, including a meaningful stretch at a cross-team level of influence (Staff, Principal or equivalent), and recent experience taking LLM-based systems into production, not only prototypes.
  • Strong fundamentals: depth in coding, plus API design, concurrency, data modelling, testing, CI/CD and containerised deployment.
  • Agentic systems in practice: orchestration and tool calling, structured outputs, multi-step planning, memory and state, and the operational reality of long-running, partially-failing workflows.
  • AI workflows: access-controlled retrieval, LLM-as-judge and its limits, drift detection, model routing, caching, compression, observability and tracing for non-deterministic systems.
  • Influence without authority: aligning multiple stakeholders, writing documents that unblock decisions, mentoring, connecting technical choices to product value, and creating an environment where respectful disagreement improves the outcome. Clear communication in English (our working language).
  • Craft culture & engineering excellence: deep, demonstrated craft sensibility; the ability not only to apply good practices but to teach them, defend them and embed them culturally; strong command of testing, software quality and observability, and comfort with data-driven steering (DORA, NFRs).