SDLC AI Agents Developer

Project overview

We are looking for an SDLC AI Agents Developer to work with one of our clients based in Saint-Ouen, in the industrial (manufacturing) sector, at Alstom, as part of a project to design, develop, and industrialize enterprise artificial intelligence solutions.

You will work within a Corporate AI / Enterprise AI organization, with the objective of designing, developing, deploying, and industrializing AI agents and multi-agent orchestrations to automate and optimize the various stages of the software development lifecycle (SDLC).

You will contribute to the evolution of an existing AI agent framework and library, their integration with software engineering and development tools, as well as their production deployment in a secure and industrialized environment.

Responsibilities

Required skills:

Profile sought:

We are looking for an experienced SDLC AI Agents Developer, holding a Master's degree in Computer Science, Software Engineering, or equivalent, with solid software development experience and operational expertise in designing and industrializing artificial intelligence agents.

Concrete experience in the development, deployment, and operation of AI agents and multi-agent systems beyond the POC stage is imperative. Experience limited to experiments or demonstrators will not be sufficient.

You have excellent command of Python, APIs, and software development best practices, including automated testing, Git versioning, packaging, and continuous integration.

You have significant expertise in generative artificial intelligence technologies, including LLMs, RAG architectures, tool calling, prompt engineering, and context engineering.

You are capable of designing robust multi-agent architectures, developing orchestration workflows, and integrating these agents with existing tools and processes.

You have experience in evolving or enriching AI agent frameworks and are able to reuse existing components to accelerate the development and industrialization of solutions.

You master collaborative development environments and associated tools, including GitHub Copilot, GitLab, and GitLab Duo, and understand the challenges of their secure integration into SDLC processes.

Practical knowledge of IBM ALM solutions, particularly RDNG, EWM, and ETM, is particularly sought after, to facilitate the integration of AI agents into software requirements management, development, and validation processes.

You understand the principles and use cases of MCP and A2A protocols and know how to identify their relevance in an AI agent architecture.

You are able to implement reproducible evaluation mechanisms, ensure traceability of actions performed by agents, and contribute to the reliability of developed solutions.

Experience with verification and validation (V&V) activities, Azure AI Foundry or Azure OpenAI environments, as well as human control and responsible AI mechanisms would be an additional asset.

Experience in an industrial, manufacturing, or large international organization environment would be particularly appreciated.

Autonomous, rigorous, pedagogical, and with excellent interpersonal skills, you know how to operate in a complex technical environment, collaborate with multidisciplinary teams, and support teams not yet familiar with Agile practices.

You are capable of acting as a technical referent for AI agent solutions, sharing your knowledge, producing quality documentation, and actively contributing to the skill development of teams.

You know how to combine technical expertise, integration capability, and operational vision to design AI solutions that are reliable, secure, maintainable, and truly usable in production.

• Design, develop, test, and deploy artificial intelligence agents to automate SDLC activities.
• Develop and industrialize multi-agent workflows and orchestrations to improve software engineering processes.
• Design AI agents involved in different SDLC stages: requirements management, code development, code reviews, verification and validation (V&V), and technical documentation.
• Extend, enrich, and maintain an existing AI agent framework and library.
• Reuse and evolve AI components, frameworks, and assets already available within the organization.
• Develop robust and maintainable AI solutions in Python.
• Design and integrate APIs for communication between AI agents and software engineering tools.
• Implement solutions based on Large Language Models (LLMs), tool calling, and RAG (Retrieval-Augmented Generation) architectures.
• Develop and optimize prompt engineering and context engineering strategies to improve agent relevance and reliability.
• Design orchestration and communication mechanisms between multiple AI agents.
• Study and utilize MCP (Model Context Protocol) and A2A (Agent-to-Agent) protocols within approved tools and environments.
• Integrate AI agents into development environments and tools like GitHub Copilot, GitLab, and GitLab Duo.
• Ensure the integration of AI agents with IBM ALM tools, including IBM Engineering Requirements Management DOORS Next (RDNG), Engineering Workflow Management (EWM), and Engineering Test Management (ETM).
• Guarantee traceability of interactions between AI agents, requirements, code, and validation activities.
• Implement automated tests and reproducible evaluation mechanisms to measure the quality, reliability, and performance of AI agents.
• Ensure versioning of code and AI agents with Git.
• Design and maintain the necessary packages for the deployment and operation of developed solutions.
• Integrate AI agents into CI/CD pipelines and ensure their secure deployment.
• Participate in the industrialization of AI solutions to move beyond POC phases and ensure their operational use.
• Implement human control, supervision, and validation mechanisms for results produced by agents.
• Apply principles of security, reliability, and responsible AI.
• Produce comprehensive technical documentation for agents, orchestrations, integrations, and deployment processes.
• Write operational guidelines and knowledge transfer materials.
• Support technical teams in adopting AI solutions and new development practices.
• Participate in the continuous improvement of SDLC processes and Agile practices.
• Foster knowledge sharing, pedagogy, and collaboration between technical and business teams.
• Proven experience in the design, development, and production deployment of AI agents and multi-agent systems (essential).
• Concrete experience in industrializing AI solutions beyond the POC stage (essential).
• Excellent command of Python and software development best practices.
• Solid experience in API development and software solution integration.
• Very good command of Large Language Models (LLMs) and their applications to AI agents.
• Expertise in the design and orchestration of multi-agent workflows.
• Good command of tool calling and interaction mechanisms between AI agents and external tools.
• Experience in implementing RAG (Retrieval-Augmented Generation) architectures.
• Very good knowledge of prompt engineering and context engineering techniques.
• Ability to develop, extend, and maintain existing AI agent frameworks and libraries.
• Good understanding of MCP (Model Context Protocol) and A2A (Agent-to-Agent) protocols.
• Mastery of Git, versioning, and source code management best practices.
• Experience in automated testing, software packaging, and development industrialization.
• Good command of continuous integration and deployment (CI/CD) processes.
• Experience with GitHub Copilot, GitLab, and GitLab Duo.
• Practical knowledge of IBM ALM tools: RDNG, EWM, and ETM.
• Good understanding of SDLC (Software Development Life Cycle) processes.
• Knowledge of requirements management, software development, code review, verification and validation (V&V) activities.
• Ability to integrate AI solutions into complex software engineering environments.
• Experience in evaluating the quality, reliability, and performance of AI agents.
• Good understanding of AI solution security, traceability, and governance issues.
• Knowledge of human control mechanisms and responsible AI principles.
• Knowledge of Azure AI Foundry and/or Azure OpenAI is appreciated.
• Good understanding of Agile methodologies and ability to support teams in their adoption.
• Ability to produce structured technical documentation and transfer knowledge.
• Professional English is essential.
• Proficiency in French is an asset.

Project details

Saint-Ouen (remote work possible).

Schedule: Hybrid

ASAP

3 months renewable

English: Essential.

• Start: 2026-11-23
• Duration: 3 mois (renouvelables)
• Location: 93400 Saint-Ouen, FR
• Languages: French