AI Engineer LLM Agents (Python) HF

SKALEET

Skaleet builds the core banking engine behind banks and neobanks: accounts payments cards. Our platform runs in production for 30 regulated financial institutions in 15 countries including Crédit Agricole Caisse dEpargne and Nirio (FDJ United) and manages over 10 million accounts.

In 2026 Euromoney named Skaleet the best banking solution in Europe. Our revenue grew by 40% in 2025. We are about 100 people based in Boulogne-Billancourt.

Our ambition: become the platform of choice for European banks and fintechs that want to replace their legacy core banking systems.

Job Description

Context

Skaleet recently created its AI Team with one clear ambition: improve our clients banking operations through AI. Running a bank means thousands of back-office operations every day; our goal is to make them faster more reliable and more scalable.

As an AI Engineer you will join the AI Team and report directly to Thomas Linck VP Platform. You will build and own Skaleets 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 Skaleets 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 Skaleets 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 Skaleets 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.

Desired Profile

You are a great match if:

Must-have

• 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

• Masters 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)

The benefits of joining Skaleet

• Hybrid work: up to 2 days of remote work per week

• 25 days of paid vacation and 12 additional days off (RTT) per year

• Health insurance: Alan Blue

• A Swile card to cover your meals on workdays

• Brand-new offices in Boulogne-Billancourt right next to Metro Line 10

Recruitment Process

1. A video call with Maxime HR Manager to get to know each other and tell you more about Skaleet our culture and values (30).

2. A video call with Louis to present Skaleets AI product vision the projects ambitions and the role you could play (30).

3. A live coding session to assess your technical skills (60).

4. A final meeting at our offices in Boulogne with Victor our Chief of Staff (60).

We look forward to discovering your profile!