AI Engineering Lead / Manager | NDA at Jobgether

, , France -

Full Time

Start Date

Immediate

Expiry Date

02 Sep, 26

Salary

0.0

Posted On

04 Jun, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

AI Engineering, Python, LLM, RAG Systems, AI Agents, Microservices, Prompt Engineering, Software Architecture, FastAPI, GitHub Copilot, CI/CD, Cloud Platforms, Backend Development, Technical Leadership, Consulting, API Design

Industry

Internet Marketplace Platforms

Description

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. \n 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. \n How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Why Apply Through Jobgether? Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time. #LI-CL1

Responsibilities

Provide technical leadership and strategic advisory to enterprise teams on adopting AI-assisted software engineering and developer productivity tools. Design and implement AI-powered applications, including RAG pipelines and agent-based architectures, while guiding system architecture and CI/CD workflows.