> Markdown version of [/jobs/ext/4554152-ai-engineer-llm-agents-python-h-f](https://www.wearedevelopers.com/jobs/ext/4554152-ai-engineer-llm-agents-python-h-f). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI Engineer - LLM Agents (Python) H/F - **Company:** Skaleet - **Location:** Boulogne-Billancourt, France (Remote available) - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Automated Storage and Retrieval Systems, Audit Trail, Automation of Tests, Memory Management, Information Retrieval, Python (Programming Language), Machine Learning, Search Technologies, Software Deployment, Software Engineering, Retrieval-Augmented Generation, Large Language Models, Backend, Information Technology, Low Latency, Restful APIs - **Published:** November 4, 2026 - **Apply:** https://www.welcometothejungle.com/en/companies/skaleet/jobs/ai-engineer-llm-agents-python-h-f_boulogne-billancourt ## About the Role * Minimum 5 years of software engineering experience, including significant hands-on experience building LLM-based agent systems in production * Strong Python backend skills: REST APIs, async, automated testing * Concrete experience with tool calling, RAG, agent context/memory management, and LLM quality evaluation * Comfortable designing and integrating complex, data-intensive production systems * Experience monitoring and optimizing LLM systems in production: observability, tracing, cost and latency control at scale * Working knowledge of guardrails and defenses against prompt injection * Fluency in French and English, both written and spoken * Master's degree in Computer Science, Machine Learning, AI, Engineering, or equivalent hands-on experience Bonus points * Strong team player with product sensitivity: you can push back on a spec that is technically unrealistic, without waiting to be asked * Proactive, autonomous, entrepreneurial mindset, at ease in a scale-up * Experience in a regulated environment (banking, insurance, healthcare) where audit trail and human control are hard constraints (a plus, not a prerequisite) ## Description As an AI Engineer, you will join the AI Team and report directly to Thomas Linck, VP Platform. You will build and own Skaleet's AI products: a suite of specialized banking agents that let back-office operators understand, analyze and act on the platform in natural language, plus AI-powered automations that take over recurring operational processes end to end. You will ship AI into production banking environments, where "mostly right" is not an acceptable bar. Your future missions Architecture & delivery * Build and ship Skaleet's AI products end to end, from early prototypes to production deployment * Own the technical architecture of our agentic platform and continuously improve it by integrating the latest advances in foundation models, agent frameworks and AI engineering Agents & reliability * Design reliable agentic workflows combining LLMs, tools, banking data and human oversight * Define how agents reason, retrieve context, call tools, handle failures and collaborate to complete complex banking operations * Own AI quality, observability and evaluation, using traces, user feedback, annotated datasets, LLM-as-judge, calibration against human labels and regression gates Integration & data * Build the integration layer between agents and Skaleet's platform: MCP servers and APIs, production-grade authentication, permission management, error handling, retries, idempotency and structured outputs * Develop the context and retrieval systems powering our agents: embeddings, vector search, hybrid retrieval, reranking and knowledge ingestion over Skaleet's product documentation and clients' business processes * Work closely with data engineers to make banking data usable by AI systems: data models, pipelines, interfaces, tenant isolation Security & compliance * Implement the safeguards required for banking use cases: human validation gates, permission scoping, tenant isolation, audit trails, explainability, safe failure modes Product & iteration * Prototype quickly, iterate with banking operators, identify high-value use cases and improve the product based on real operational feedback * Evaluate and integrate the best available AI models and technologies based on quality, latency, cost, security and regulatory constraints This role is about building systems on top of existing foundation models, not training models from scratch.