Forward Software Engineer, Data (AI)

Location: Hybrid in Paris, France, with London as another location

Company

Mistral AI provides full-stack AI solutions, including frontier models, developer tools, applications, and compute, for enterprise customers in high-stakes industries.

What you will do

• Build AI systems end to end, from prototypes through production.
• Design data architecture covering ingestion, processing, storage, data models, and ontologies.
• Build distributed pipelines for large volumes of documents, code, logs, and multimodal content supporting retrieval, agentic workflows, and fine-tuning.
• Develop reusable patterns and platforms from customer solutions, while designing for throughput, latency, cost, and failure recovery.
• Implement data governance, including ownership, access control, lineage, retention, and privacy for sensitive enterprise data.
• Build evaluation loops with human and LLM labeling, versioned datasets, and quality-drift checks; collaborate with researchers, engineers, and customer-facing teams.

Requirements

• Full-stack delivery ability with NodeJS technologies such as NextJS, Express, or Fastify, or Python technologies such as FastAPI.
• Confidence with TypeScript and React/NextJS or similar technologies.
• 5+ years of experience building and running production data-intensive pipelines with distributed processing tools such as Spark, Ray, Beam, or Dask, and orchestration tools such as Airflow, Dagster, or Prefect.
• Experience working with both structured and unstructured data.
• Experience with retrieval-augmented generation, agentic use cases, or LLM evaluation, with an understanding of how data quality drives model quality.
• Autonomous problem-solving, ownership of outcomes, and clear communication with technical and non-technical audiences.
• Fluent English.
• Ability to ship incrementally, prioritize time to value, and make and articulate product-technical tradeoffs.

Nice to have

• Passion for graph-based systems such as Neo4j and ontology design.
• Hands-on experience building data pipelines for LLM training, fine-tuning, or evaluation.
• Open-source contributions, particularly in data or LLMs.
• Experience with data governance, privacy requirements such as GDPR, secure data handling, CI/CD, or infrastructure as code.
• Affinity for security engineering.

Culture & Benefits

• Output-focused environment where shipped results matter more than time spent.
• Low-bureaucracy, direct-feedback culture with high standards and low ego.
• Collaborative work with distributed teams across Europe, North America, Asia, and the Middle East.
• Benefits may include healthcare, parental leave, retirement plans, relocation support, wellness programs, and meal and transportation allowances, depending on location.