Lead AI Engineer

Solution Architecture & Technical Ownership

Collaborate with the Director of Generative AI to design end-to-end AI solution architectures — including agentic workflows, RAG pipelines, LLM integrations, and enterprise system connectors — and own the technical execution of those designs.

Independently architect solutions for assigned use cases, presenting designs for review and approval prior to development; progressively take on broader architectural ownership as familiarity with the team's standards and systems deepens.

Evaluate Azure platform services and select appropriate hosting, storage, and compute patterns (Web Apps, Function Apps, CosmosDB, Container Registry, AI Search, Key Vault, and others) for each solution's specific requirements.

Uphold, refine, and enforce engineering standards across the development team: code structure and quality, security and access control, testing and validation, deployment practices, and technical documentation — building on the foundation established by the Director of Generative AI.

Deployment, Operations & Security

Own the deployment, configuration, and operational management of AI services in Microsoft Azure, ensuring solutions meet enterprise security requirements including private networking, role-based access control, and secrets management.

Proactively monitor deployed services, address performance or reliability issues, and maintain documentation to support long-term maintainability and team knowledge continuity.

Partner with IT, infrastructure, and security stakeholders to ensure solutions align with Legrand's enterprise architecture and compliance standards.

Development

Contribute hands-on development work on priority projects — particularly back-end services, agentic framework implementations, and complex API integrations.

• Build, review, and maintain Python-based services (FastAPI)
• Automation workflows
• Integration pipelines; work across the stack as needed including front-end components (React/Vite/Chakra UI) and Node.js integrations.

Team Leadership & Mentorship

Directly lead the AI development team, providing day-to-day technical direction, task prioritization guidance, and active unblocking.

Take ownership of the team's agile practices — including sprint planning, standups, and retrospectives — ensuring ceremonies run consistently and the team operates with clarity, shared context, and momentum; may delegate facilitation to senior team members as appropriate.

Mentor developers at all levels through pair programming, code review, technical coaching, and structured feedback — with particular focus on growing architectural thinking and independent problem-solving.

Serve as the primary technical escalation point for the development team.

Cross-Functional Collaboration

Serve as the development team's steward of the AI-assisted solution refinement process: ensuring the team correctly applies established refinement workflows, maintaining the quality and completeness of work items in Azure DevOps, and continuously identifying opportunities to further improve and automate the refinement pipeline — in partnership with the Director of Generative AI and AI Program Manager.

Support the AI Program Director and Director of Generative AI in assessing technical feasibility, effort estimation, and risk identification for proposed use cases.

Communicate technical decisions and architectural tradeoffs clearly to both technical peers and non-technical stakeholders.