Enterprise AI Deployment Engineer: Outcomes & Scale

Accenture France; Paris; On-site; EUR 70,000 - 100,000; Full time

Job summary

Accenture France is seeking a Forward Deployed AI Engineer who sits with client teams to deploy and operationalize AI platforms in real enterprise environments. You own outcomes such as time-to-value, reliability, adoption velocity, and scalability, not just milestones.

You'll design architectures across the enterprise stack, translate tech into business impact for CTO/CFO/CISO, and create reusable patterns and accelerators that clients own after you leave.

Qualifications

• 3-5 years engineering experience with cloud-native systems (APIs, microservices, containerization).
• Minimum 1 year of deep expertise in designing and deploying agentic solutions in production.
• Minimum 3 years of experience with AI platforms (OpenAI, Claude, Vertex AI) and multi-provider pipelines.
• Experience deploying to production with CI/CD and infrastructure as code (Terraform, Helm).
• Proven ability to articulate business value to executive stakeholders.

Responsibilities

• Embed directly with client teams to deploy and operationalize AI platforms inside enterprises.
• Own production outcomes end-to-end: time-to-value, reliability, adoption velocity, scalability.
• Prototype rapidly to move from problem to production within days to weeks.
• Design and govern AI architectures across identity, data, security, and workflow layers.
• Translate technical architecture into business impact for CTO, CFO, and CISO.
• Build reusable patterns and accelerators for client ownership after deployment.
• Lead design workshops, proofs of concept, and architecture reviews with client teams.
• Codify delivery learnings to scale across engagements within the FDE practice.

Skills

AI deployment

Cloud-native systems

OpenAI / LLM platforms

CI/CD

Terraform / IaC

Kubernetes

Stakeholder communication

Tools

Terraform

Helm

Kubernetes

CI/CD tools

Job description

Accenture France is seeking a Forward Deployed AI Engineer who sits with client teams to deploy and operationalize AI platforms in real enterprise environments. You own outcomes such as time-to-value, reliability, adoption velocity, and scalability, not just milestones.

You'll design architectures across the enterprise stack, translate tech into business impact for CTO/CFO/CISO, and create reusable patterns and accelerators that clients own after you leave.