AI Engineering Lead / Manager | NDA

This position is posted by Jobgether on behalf of a partner company. We are currently looking for an AI Engineering Lead / Manager | NDA in France. This is a high-impact consulting opportunity for an experienced AI engineering leader to help transform how modern software teams build, deliver, and scale products using AI-assisted development practices. In this role, you will work at the intersection of software engineering, artificial intelligence, and engineering productivity, guiding enterprise teams through the adoption of LLM-powered tools and workflows. You will operate in a client-facing environment, collaborating closely with engineers, architects, product leaders, and consulting stakeholders. The engagement blends strategic advisory responsibilities with hands-on technical delivery, including the design of AI applications, RAG systems, and agent-based architectures. This is an ideal role for a senior engineer or architect who thrives in fast-paced consulting environments and enjoys shaping engineering excellence at scale. The assignment offers exposure to cutting-edge AI technologies and real-world enterprise transformation challenges.

Accountabilities

• Provide technical leadership and advisory support to engineering and consulting teams on AI-assisted software engineering, developer productivity, system architecture, and modern engineering practices.
• Guide the adoption of AI tools such as Claude Code, Cursor, Codex, and GitHub Copilot to improve software development workflows and efficiency.
• Define and refine architectural approaches for systems, including microservices, APIs, data flows, integrations, and CI/CD pipelines.
• Translate business requirements into clear technical designs and implementation strategies aligned with delivery goals.
• Spend a portion of time hands‑on building and supporting AI-powered applications, including LLM-based systems, RAG pipelines, and AI agents.
• Design, implement, and optimize retrieval-augmented generation (RAG) systems with a focus on performance, cost efficiency, and accuracy.
• Contribute to engineering execution through code reviews, testing strategies, documentation, and implementation support.
• Advise on engineering best practices including automated testing, secure development, clean code principles, and scalable delivery workflows.
• Collaborate with cross‑functional stakeholders including product, design, architecture, and platform teams in a client‑facing environment.
• Support continuous improvement of engineering maturity across people, processes, and technology.

Requirements

• Strong background in software engineering, backend development, full-stack engineering, or software architecture.
• Extensive hands‑on experience with Python in production environments.
• Experience designing and developing microservice-based systems using REST, GraphQL, or gRPC APIs.
• Familiarity with API frameworks such as FastAPI, OpenAPI, Swagger, or similar technologies.
• Practical experience with AI‑assisted development tools such as GitHub Copilot, Cursor, Claude Code, Codex, or equivalents.
• Hands‑on experience with LLM-based applications, including prompt engineering, structured prompting, RAG systems, and AI agents.
• Deep understanding of transformer-based models and large language model architectures.
• Experience building and optimizing retrieval-augmented generation pipelines, including handling hallucination risks and performance trade‑offs.
• Strong understanding of software engineering fundamentals, including data structures, algorithms, testing strategies, and OOP principles.
• Knowledge of tokenization, context limitations, model behavior, and cost-performance optimization in LLM systems.
• Ability to translate complex business needs into technical solutions and implementation roadmaps.
• Strong communication skills with the ability to explain technical concepts to both technical and non‑technical stakeholders.
• Experience working in client‑facing or consulting environments is highly desirable.
• Comfortable working with partial overlap with US time zones.
• Experience with cloud platforms (AWS, GCP, or Azure), databases (SQL or NoSQL), or enterprise environments is a plus.

Benefits

• Opportunity to work on cutting‑edge AI engineering transformation projects for enterprise clients.
• High‑impact consulting engagement at the intersection of AI, software engineering, and developer productivity.
• Exposure to advanced LLM applications, RAG architectures, and AI agent systems in real‑world environments.
• Client‑facing role with significant ownership and visibility across technical and business stakeholders.
• Flexible consulting engagement structure with international collaboration.
• Opportunity to shape engineering practices and AI adoption strategies at scale.
• Hands‑on experience with modern AI tooling and enterprise‑grade system design.
• Exposure to global consulting environments and large‑scale transformation programs.
• Competitive compensation aligned with senior‑level consulting expertise and AI engineering experience.