About Idun
Idun Group is an independent AI consultancy. We measure how AI is actually used inside our clients, from the logs their platforms already produce, then help them industrialise what works. More than 40 AI assessments in a year; our references include LVMH and L'Oréal. It is tooled consulting: our software, Idun Cockpit, measures real usage, then we say what to industrialise, consolidate or cut. Idun is backed by Wilco, IMT Starter, Polytechnique X-UP and La French Tech.
The role
Most enterprise AI projects stall not at the model layer but at the infrastructure layer. The data team has a prototype; the platform team has no idea how to operate it; the security team has a list of blockers that nobody has worked through. We exist to close that gap.
As an AI Platform Engineer, you join an engagement as the technical anchor. You deploy the Idun Platform into the client's environment (cloud or on-prem, whatever their constraints demand) and you build the first agents with their team, not for them. The difference matters. By the end of an engagement, the client's engineers own the patterns, the deployment pipeline, and the production readiness checklist. You are the person who made that transfer real.
This is a senior-to-staff level role. You will hold technical conversations with Tech Leads, platform engineers, and infrastructure architects. You will push back when a proposed architecture doesn't scale. You will translate a vague "we want AI" mandate into a first working agent with proper observability, guardrails, and access control. The work is demanding and genuinely interesting. EU enterprises deploying agents under GDPR and the EU AI Act are solving problems that most of the industry has not figured out yet.
What you'll do
- Deploy and configure the Idun Platform in client environments, working around real security, network, and infrastructure constraints: cloud (GCP, Azure, AWS), on-prem Docker, air-gapped.
- Co-build the first agents and first production use cases with client engineering teams using LangGraph, Google ADK, or Haystack.
- Set up the full industrialisation stack: OpenTelemetry tracing to Langfuse or Phoenix, memory backends, guardrails policies, OIDC/RBAC integration, CI/CD pipelines, automated tests.
- Lead technical scoping sessions: translate business requirements into agent architecture, data flow diagrams, and a deliverable component list.
- Define engineering best practices for the client team: code organisation, configuration management, debugging playbooks, testing strategy, deployment runbooks.
- Build reusable frameworks and templates that leave the client capable of extending the platform independently after the engagement closes.
- Document deployment patterns, write post-engagement handoff guides, and contribute findings back into Idun's shared implementation knowledge base.
Stack & environment
You will work across this stack on every engagement:
- Python, FastAPI, Pydantic, PostgreSQL: the core runtime and data layer
- Docker, Git, CI/CD, REST APIs, YAML: configuration-driven deployment on any infrastructure
- LangGraph, Google ADK, Haystack: the three primary agent frameworks we deploy against
- MCP, A2A, streaming / SSE: protocol-level interop between agents, tools, and frontends
- OpenTelemetry, Langfuse, Phoenix: the observability chain; Langfuse and Phoenix are the primary trace UIs
- OIDC, RBAC, SSO: auth integration with whatever identity provider the client already runs (Google, Microsoft, ADFS)
The code of the Idun open-source platform is public. The clients are deploying on their own infrastructure. You will sometimes be the first person in the building who has done this before, and that is normal and expected.
Profile we're looking for
- Senior engineering background: 5+ years building and shipping production systems, at least 2 years in AI/ML or agentic systems. You can hold a peer-level technical conversation with a Staff Engineer.
- Hands-on with at least one of LangGraph, Google ADK, or Haystack in a production setting, not just a tutorial. Bonus: you have a mental model of where each framework fits and where each struggles.
- Comfortable owning the full stack on an engagement: platform configuration, agent code, observability wiring, auth integration, delivery pipeline, documentation. You do not wait to be handed a sub-task.
- Fluent in the EU regulatory context: you understand what GDPR data residency means for an agent's memory backends and what the EU AI Act's transparency requirements mean for observability. Clients ask these questions; you have the answers.
- Bilingual French/English (working language is mixed on most engagements; client communication is primarily French for Paris accounts).
Why join this role
- Depth of technical ownership. You are not embedded in a feature squad. You own the full technical surface of an engagement: architecture, code, delivery, knowledge transfer. Few consulting roles give this level of autonomy this early.
- Genuine EU AI frontier. European enterprises deploying agents under GDPR + EU AI Act constraints are solving problems the industry has not standardised. Your solutions become the patterns that other teams follow.
- Equity. As an early team member, you receive equity in Idun Group alongside your salary.
- Soutiens and network. Idun is backed by Wilco, IMT Starter, Polytechnique X-UP, and La French Tech. You get access to the people and programmes that come with that network.