Senior AI Solutions Architect: GenAI & Multi-Agent Systems

Infosys; Marseille; Sur place; EUR 90 000 - 130 000; Plein temps

Résumé du poste

Infosys Marseille is seeking a senior AI software engineer to guide development of GenAI features, own solution design, and ensure architecture and coding standards across scalable AI deployments. You will collaborate with teams to deliver production-ready AI applications and system integrations.

The role emphasizes memory management, RAG workflows, tool calling, and responsible AI practices, with focus on observability and governance using LangFuse and related tools.

Qualifications

• 8+ years of software development experience.
• Expert Python development and AI feature implementation.
• Experience building and deploying GenAI solutions using LLM APIs and AI SDKs.
• Design of intelligent agent workflows with memory, prompt orchestration, and RAG.
• Implementation of Responsible AI, guardrails, and observability.
• Familiarity with development tools like GitHub Copilot, Codex, and other AI coding assistants.
• Strong communication and stakeholder management skills.

Responsabilités

• Provide technical direction to the development team.
• Own solution design and implementation decisions.
• Ensure adherence to architecture and coding standards.
• Build Core AI features.
• Qualify, route and resolve defects.

Connaissances

Python

Mistral Doc Processing

LLM APIs

LangGraph

LangChain

Semantic Kernel

AWS

GCP

Docker

Kubernetes

CI/CD

Git

DevOps

Multi-agent systems

Memory management

RAG

Tool calling

Prompt orchestration

Context engineering

Observability

LangFuse

Outils

Cursor

Codex

Claude Code

GitHub Copilot

Description du poste

Infosys Marseille is seeking a senior AI software engineer to guide development of GenAI features, own solution design, and ensure architecture and coding standards across scalable AI deployments. You will collaborate with teams to deliver production-ready AI applications and system integrations.

The role emphasizes memory management, RAG workflows, tool calling, and responsible AI practices, with focus on observability and governance using LangFuse and related tools.