Forward Deployed AI Engineer

About the role

Accenture is hiring a Forward Deployed AI Engineer in Paris. This is not a consulting, project delivery or research role: it is a production engineer embedded inside a client's enterprise, working alongside its teams to make complex AI platforms work in real, messy environments. The engineer owns outcomes such as time-to-value, adoption, reliability and scalability, and joins the Reinvention Deployment Engineering pods, which are building the largest FDE capability in the services industry.

Key responsibilities

• Embed with client engineering and business teams to deploy, scale and operationalize AI platforms (Anthropic, OpenAI, Microsoft, Google, Salesforce, SAP or Palantir) in enterprise settings.
• Own production outcomes end-to-end, with business metrics attached, not just delivery milestones.
• Move from an ambiguous business problem to a working production system through rapid experimentation, from days to prototype to weeks to production-ready.
• Design and govern AI architectures across the full enterprise stack: identity, data, security, governance, platform layer and workflow integration.
• Translate technical architecture into business impact for the client CTO, CFO and CISO, shaping use-case roadmaps, ROI backlogs and AI adoption strategy.
• Build reusable patterns, playbooks and accelerators that the client owns after you leave.
• Lead design workshops, proofs of concept, architecture walkthroughs and code-with sessions with client teams.
• Codify patterns and delivery learnings that scale across engagements and grow the FDE practice.

Required profile

• 5 years of engineering experience with cloud-native systems (APIs, microservices, containerization, serverless).
• At least 1 year of deep expertise designing and deploying agentic solutions (agents, orchestration, context engineering, RAG, workflows) in production.
• At least 3 years of experience with AI platforms (OpenAI, Claude, Vertex AI, plus open-source models), including abstraction layers for multi-provider pipelines.
• At least 10 years of experience deploying to production, CI/CD, infrastructure as code, monitoring and debugging.
• Demonstrated end-to-end delivery ownership in a client-embedded environment; internal projects, vendor labs or team-only deployments do not qualify.
• Ability to quantify deployment impact in terms a CFO recognizes, and experience presenting to CTO, CFO or CISO level stakeholders.

Required skills

• Cloud-native systems: APIs, microservices, containerization, serverless
• Agentic solutions: agents, orchestration, context engineering, RAG, workflows
• AI platforms: OpenAI, Claude, Vertex AI, open-source models
• CI/CD, Terraform, Helm, monitoring and debugging