AI Engineer - LLM Agents (Python) H/F

Skaleet; Boulogne-Billancourt; Hybrid; EUR 90,000 - 130,000; Full time

Benefits offered by this job

Hybrid work: up to 2 days of remote"

25 days of paid vacation and 12 RTT

Health insurance: Alan Blue

Swile card to cover meals

Brand-new offices in Boulogne-Billanc"

Job summary

Skaleet, a Boulogne-Billancourt based fintech, has created an AI Team tasked with building banking agents and automations that operate in production. As an AI Engineer you will join this team and own AI products from prototype to production, integrating LLMs, tools and data across banking workflows.

You will design reliable agent workflows, define reasoning and retrieval strategies, ensure observability and guardrails, and collaborate with data engineers to put banking data to work.

Qualifications

• Minimum 5 years of software engineering, with production LLM-based agent systems.
• 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.

Responsibilities

• Build AI products end to end from prototype to production.
• Own the architecture of the agentic platform and integrate new LM advances.
• Design reliable agentic workflows with LLMs, tools, data and human oversight.
• Define how agents reason, fetch context, call tools and handle failures.
• Ensure AI quality, observability and evaluation with traces and datasets.
• Develop integration between agents and Skaleet's MCP servers and APIs.
• Collaborate with data engineers to make banking data usable for AI.
• Implement safeguards: gates, permissions, audit trails, explainability.
• Prototype quickly; iterate with operators based on feedback.
• Evaluate models for quality, latency, cost, security and compliance.

Skills

Python backend

REST APIs

Async

Automated testing

Tool calling

RAG

Agent context management

LLM quality evaluation

Observability

Tracing

Guardrails

French & English

Master's degree in CS/ML/AI

Education

Master's degree in Computer Science / ML / AI

Job description

[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 d'Epargne 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 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.

[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

• 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)

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 Skaleet's AI product vision, the project's 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!