Software Engineer (GenAI / MLOps & ModelOps) - AI-Share Team

DataGalaxy; Paris; Hybride; EUR 90 000 - 115 000; Plein temps

Avantages offerts par ce poste

Flexible working hours

Remote work options

Health insurance

Meal vouchers

Public transport reimbursement

Holiday bonus

Quarterly team events

Holiday Bonus

Quarterly events

Competitive remuneration

Opportunity to join a French start-up

Résumé du poste

A pioneering data governance startup is looking for an MLOps engineer to enhance its platform with reliable Generative AI capabilities. The role involves developing production workflows, integrating cloud services, and collaborating with cross-functional teams. Ideal candidates will have solid Python experience and familiarity with cloud environments and CI/CD processes. Work is hybrid with flexible hours, and benefits include a competitive salary, health insurance, meal vouchers, and opportunities for work-life balance.

Qualifications

• Professional experience delivering production software in Python.
• Familiarity with CI/CD and production environment constraints.
• Interest in MLOps and managing cost/latency trade-offs.

Responsabilités

• Contribute to ModelOps platform and automate deployments.
• Implement CI/CD workflows adapted for AI.
• Develop GenAI features within the platform.
• Improve traceability of AI assets (configs, prompts, versions) for governance and debugging.
• Add observability for GenAI workloads: latency, availability, cost signals, dashboards/alerts.
• Develop and improve GenAI features within the platform (agent, RAG pipelines, MCP server).
• Work with Product/Data/Engineering to integrate GenAI capabilities in a maintainable way.

Connaissances

Python programming

CI/CD practices

Debugging

Cloud services

MLOps

Polyglot environment

Kubernetes

Outils

Docker

Kubernetes

Terraform

OpenTelemetry

FastAPI

Git

Description du poste

Since day one, DataGalaxy has been guided by a simple conviction: data creates value when people align on it, adopt it, and turn it into business outcomes. Metadata is not the destination. It is the foundation that makes this possible. That's why DataGalaxy built the value governance platform, a business-first approach that connects data and AI strategy to execution, IT teams to business teams, and metadata to business outcomes. The platform includes two core products: DataGalaxy Catalog and DataGalaxy Portfolio Center. Catalog is a metadata center to provide context, build trust, and ensure compliance. Portfolio Center is a product management tool to show value creation from initiatives and champion alignment from C-levels to business stakeholders. Founded in France and expanding rapidly across Europe and the United States, DataGalaxy is trusted by over 200 global enterprises, including Dior, Airbus, and SwissLife. The company is committed to driving data culture and literacy by helping organizations deliver metadata to the agents and value to the people.

Our values:

Be intentional. Be clear. Be bold. Be humble.

About The Role

Join the AI-Share team to help build and operate the foundations that power our Generative AI features (LLM, RAG, agents) inside the DataGalaxy data governance platform. This role focuses on MLOps / ModelOps delivery: making GenAI capabilities reliable in production (deployment, monitoring, cost control, traceability), while collaborating with product engineering teams across a polyglot stack.

You don't need to match every item below - we value curiosity, eagerness to learn, pragmatism, and steady progress!

What You'll Do (with Support From Senior Engineers)

MLOps / ModelOps (core)

• Contribute to the evolution of our ModelOps platform for GenAI: provider integrations, configuration, deployment automation, and operational tooling
• Help implement practical patterns for running GenAI workloads in production: evaluation, versioning, reproducibility, safe rollouts/rollbacks, and environment management
• Build and improve CI/CD workflows adapted to AI: packaging, automated checks, evaluation steps (when applicable), deployment, and rollback
• Improve traceability of AI assets (configs, prompts/templates when applicable, evaluation outputs, versions) to support governance and debugging
• Add and maintain observability for GenAI workloads: latency, availability, usage/cost signals, and quality-related indicators (dashboards/alerts)

GenAI feature development & platform integration (core)

• Develop and improve GenAI features within the platform (agent, RAG pipelines, MCP server): new capabilities, prompt engineering, bug fixes, and client-facing improvements
• Work closely with Product / Data / Engineering to integrate GenAI capabilities into the platform in a maintainable way
• Participate in code reviews, documentation, and post-incident follow-ups (RCA / action items), with guidance from the team

Tech environment (high level)

• Python for MLOps tooling, evaluation, automation, and integrations
• Cloud services and managed GenAI providers (e.g., Azure AI Foundry, AWS Bedrock, GCP Vertex)
• CI/CD, containers (Docker), observability tooling
• A polyglot product stack (e.g., backend services and front-end surfaces owned by other squads)

Requirements

Must-have

• Professional experience delivering production software in Python (services, tooling, automation): comfortable reasoning about service design, maintainability, and code quality
• Familiarity with CI/CD and shipping changes to production (pipelines, environments, rollbacks, release hygiene)
• Comfortable with cloud/production constraints: reading logs/metrics, debugging issues, improving reliability over time
• Interest in MLOps / GenAI operations (deploying providers/models, evaluating changes, managing latency/cost trade-offs)
• Comfortable working in a polyglot environment: you can read/understand code and interfaces beyond Python, and you have experience with at least one other language (e.g., C#, TypeScript, Java/Kotlin, Go)

Nice-to-have (big plus)

• Comfortable working with AI-assisted development tools (e.g. coding agents, copilots) as part of your daily workflow, and open to evolving your practices as these tools mature
• Hands-on exposure to LLM/RAG/agents in real projects (prompt/version management, evaluation approaches, basic safety/guardrails)
• Familiarity with managed GenAI platforms (Azure AI Foundry / Bedrock / Vertex) or similar services
• Exposure to self-hosted inference servers (e.g. vLLM) and/or multi-model routing solutions (e.g. LiteLLM) and understanding architecture trade-offs with managed providers and for potential on-premises deployments
• Experience with containers and orchestration (Docker, Kubernetes), plus service-to-service patterns
• Infrastructure-as-code experience (Terraform or equivalent)
• Observability experience (OpenTelemetry, dashboards/alerting) and cost monitoring
• Familiarity with Python API frameworks (e.g. FastAPI) and software design principles (SOLID, modular architecture, dependency injection)
• Prior exposure to parts of our broader stack (e.g., .NET, Angular) is welcome but not required

Benefits

• Offices in the heart of Lyon (Part Dieu) and Paris (2ème arr.)
• Flexible working hours ("forfait jour")
• Remote work at will & 2.70€ net per day worked from home
• 2 weeks of working from anywhere 🌍
• Health insurance Apicil covering you and your family
• Meal vouchers (Swile card of 9€/day)
• Public transport 50% reimbursement, 100% reimbursement for your bike subscription
• Holiday Bonus 🏝️
• Quarterly team events and seminars
• An attractive remuneration according to your performance and your potential
• A real opportunity to join a French start-up that is a pioneer in its market 🚀

At DataGalaxy, we believe diversity is a strength that fuels our mission. DataGalaxy is committed to ensuring everyone feels included, valued, and empowered at work. As an equal opportunity employer, we welcome all qualified applicants regardless of age, color, family or marital status, gender identity, national or social origin, physical or mental disability, or sexual orientation or any other characteristic protected by applicable laws.