Software Engineer, Data

Mistral AI

. Build AI systems end to end, from first prototype to production .

Posted 11/6/2026full-timeParis • FranceMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and running production data-intensive pipelines, with a strong focus on data governance, quality, and architecture. Proficient in NodeJS, Python, and TypeScript, with hands-on experience in LLM training and evaluation.

Highest-signal resume keywords

Production Data PipelinesNodeJS or Python ProficiencyData Governance and PrivacyLLM Evaluation ExperienceDistributed Processing and Orchestration

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

NodeJSPythonTypeScriptReactData ArchitectureData PipelinesLLM TrainingData QualityGraph-Based SystemsOntology Design

Soft Skills

Clear CommunicationAutonomous WorkCollaboration

Tools & Technologies

NextJSFastAPICI/CDInfrastructure as CodeData Governance Tools

Industry Keywords

Data GovernanceGDPRRetrieval-Augmented GenerationAgentic WorkflowsQuality-Drift Checks

Tech Stack

Tools & technologies

Next.jsNode.jsPythonReactTypeScript

About the role

Key responsibilities & impact

Build AI systems end to end, from first prototype to production
Design data architecture covering ingestion, processing, storage, data models, and ontologies
Build distributed pipelines processing large volumes of documents, code, logs, and multimodal content for retrieval, agentic workflows, and fine-tuning
Turn customer-specific solutions into reusable patterns and platforms
Design systems for throughput, latency, cost, and failure recovery under real load
Build data governance into systems, including ownership, access control, lineage, retention, and privacy
Build evaluation loops with LLM and human labeling, versioned evaluation datasets, and quality-drift checks
Set standards for designing and shipping data systems
Collaborate with researchers, engineers, and customer-facing teams
Work directly on customer engagements when needed

Requirements

What you’ll need

5+ years of experience building and running production data-intensive pipelines with distributed processing and orchestration tools
Proficient in NodeJS (e.g. NextJS, Express, Fastify) or Python (e.g. FastAPI)
Confident with TypeScript and React/NextJS or similar
Experience with structured and unstructured data
Experience with retrieval-augmented generation, agentic use cases, or LLM evaluation
Clear understanding of how data quality drives model quality
Ability to work autonomously and own outcomes
Clear communication with technical and non-technical audiences
Fluent in English
Comfortable making and articulating product-technical tradeoffs
Passion for graph-based systems and ontology design
Hands-on experience building data pipelines for LLM training, fine-tuning, or evaluation
Contributions to open-source projects, particularly in data or LLMs
Hands-on experience with data governance and privacy requirements such as GDPR
Experience with secure data handling, CI/CD, and infrastructure as code, or affinity for security engineering

Benefits

Comp & perks

Healthcare coverage
Parental leave
Retirement plans
Relocation support
Wellness programs
Meal allowances
Transportation allowances
Other location-specific perks
What matters is what you ship, not the time you spend on it