Software Craftsperson – Python & AI

About the role

We are looking for a Software Craftsperson specialized in Python and AI to join a partner company in France. The role sits at the intersection of software engineering and AI‑native development, where you will build high‑quality, scalable systems while using AI as a co‑creator throughout the development lifecycle.

Key responsibilities

• Own the end‑to‑end lifecycle of engineering initiatives, ensuring delivery readiness, production stability and smooth execution.
• Design and deliver scalable, maintainable features with strong architectural focus.
• Identify technical, product and process inefficiencies and proactively drive improvements.
• Actively use AI tools to accelerate design, development, testing, debugging and delivery workflows.
• Contribute to developer experience and delivery improvements using modern practices such as DORA metrics and flow optimisation.
• Support estimation, planning and vertical slicing to ensure incremental delivery of value.
• Provide technical leadership through mentoring, feedback and guidance.
• Collaborate with stakeholders to clarify requirements, resolve ambiguity and align on outcomes.
• Influence engineering standards including code quality, testing approaches and system design practices.

Required profile

• Minimum 4 years of software engineering experience, including at least 2 years building AI/ML systems in production.
• Strong proficiency in Python (and willingness to work with TypeScript) and solid fundamentals in data structures, algorithms and software design.
• Hands‑on experience building production applications using large language models (e.g., GPT, Claude) for document processing, extraction or classification.
• Proven expertise in prompt engineering and improving structured outputs from LLMs for real‑world business use cases.

Required skills

• Python
• TypeScript
• Data structures & algorithms
• Software design principles
• Large language models (GPT, Claude, etc.)
• Prompt engineering
• LangChain, LlamaIndex or similar orchestration frameworks
• Vector databases (Pinecone, Qdrant, PgVector)
• LLMOps practices (CI/CD, prompt versioning, evaluation, monitoring, cost optimisation)
• Scalable backend systems and API design
• DORA metrics and flow optimisation