AI / ML Engineer H/F

Company Overview

Skaleet is a dynamic and fast-growing tech company specializing in Core Banking Solutions. We help financial institutions in 15 countries to innovate, scale, and deliver superior banking experiences to millions of end-customers. At Skaleet, we thrive on collaboration, creativity, and a shared passion for redefining the future of banking. Join us in our journey to transform the financial industry! Our ambition is to build the pan-European leader in modern Core Banking and to become the platform of choice for European financial institutions, helping them modernise infrastructure, scale operations, and launch new banking services rapidly.

Responsibilities

• Build and ship Skaleet’s AI products end to end, from early prototypes to production deployment. Own the technical architecture of the agentic platform and continuously improve it by integrating the latest advances in foundation models and AI engineering.
• 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 evaluation, calibration against human labels and regression gates to ensure agent behaviour remains reliable as models and prompts evolve.
• Build the integration layer between agents and Skaleet’s platform, including MCP servers and APIs, with production-grade authentication, permission management, error handling, retries, idempotency and structured outputs.
• Develop the context and retrieval systems powering our agents, including 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, defining the data models, pipelines and interfaces agents need to access clean, accurate and tenant-isolated operational data.
• Implement the security, compliance and operational safeguards required for banking use cases, including human validation gates, permission scoping, tenant isolation, audit trails, explainability and safe failure modes.
• Prototype quickly and iterate with banking operators, identifying high-value use cases, putting early versions in users’ hands and improving 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. Focus on building systems on top of existing foundation models rather than training models from scratch.

Desired Profile

• Education: Master's degree in Computer Science, Machine Learning, Artificial Intelligence, Engineering, or equivalent hands‑on experience.
• Experience: minimum of 5 years of experience, including significant hands‑on experience building LLM‑based agent systems in production. Prior experience in fintech or banking is a plus.
• Technical: strong Python backend skills (REST APIs, async, testing); concrete experience with tool calling, RAG, agent context/memory management, and LLM quality evaluation; comfortable designing and integrating complex, data‑intensive production systems.
• Production maturity: experience monitoring and optimizing LLM systems in production – observability/tracing, cost and latency control at scale.
• Security & safety: working knowledge of guardrails and defenses.
• Languages: Fluency in French and English, written and spoken.
• Interpersonal skills: strong ability to collaborate with diverse teams, an excellent team player; product sensitivity – able to push back on a functional spec when technologically unrealistic; proactive and able to work independently.
• Thrives on challenges, entrepreneurial mindset, and enjoys the energy of scale‑ups.
• Bonus points: experience in a regulated environment (banking, insurance, healthcare) with audit trail and human control constraints.

Benefits

• Remote Policy: work from home 2 days per week, offering flexibility and balance.
• 25 days of paid vacation and 12 additional days off per year.
• Health insurance: Alan Blue.
• Lunch Matters: Swile card to cover meals on workdays.
• An entrepreneurial mindset and strong team spirit.
• Beautiful, brand‑new offices located in Boulogne‑Billancourt, next to Metro Line 10.