Forward Deployed AI Engineer

Accenture PLC; Paris; On-site; EUR 90,000 - 140,000; Full time

Job summary

Accenture PLC is seeking Forward Deployed AI Engineers to join our Reinvention Deployment Engineering pods in Paris. You will embed with client teams to deploy AI platforms like OpenAI, Anthropic, Microsoft, Google, and more into production environments.

You will own end-to-end outcomes, drive rapid prototyping to production, and design architectures across the full stack, translating tech work into measurable business value for CTOs, CFOs, and CISOs.

Qualifications

• 3-5 years engineering experience with cloud-native systems and APIs.
• 1+ year designing and deploying agentic solutions in production.
• 3+ years of experience with AI platforms (OpenAI, Claude, Vertex AI) and open-source models.
• 10+ years deploying to production with CI/CD and infrastructure as code.
• Proven end-to-end delivery ownership in client-embedded environments.
• Ability to quantify business value and communicate with senior stakeholders.
• Experience presenting to CTO/CFO/CISO level; diverse profiles welcomed.

Responsibilities

• Embed with client teams to deploy and operationalize AI platforms inside enterprise environments.
• Own end-to-end production outcomes with time-to-value, reliability, and adoption metrics.
• Prototype quickly and progress from problem to production-ready system.
• Design and govern AI architectures across identity, data, security, and platform layers.
• Translate architecture into business impact and shape ROI roadmaps.
• Create reusable patterns and accelerators for client ownership after engagement ends.
• Lead design workshops, proofs of concept, and architecture walkthroughs.
• Codify lessons to scale across engagements within the FDE practice.

Skills

Cloud-native systems

APIs

Microservices

Containerization

Serverless

Agentic solutions

RAG

Workflows

AI platforms

OpenAI

Claude

Vertex AI

CI/CD

Infrastructure as code

Terraform

Helm

Monitoring

Production deployment

Stakeholder communication

Tools

Terraform

Helm

Job description

The market is beginning to understand what leading technology companies have demonstrated: AI products fail not because the models are weak but because deployment is broken. The gap between a successful AI pilot and an AI capability that scales is bridged by engineers who can translate platform capability into measurable business value inside a real enterprise environment. That is this role.

Forward Deployed AI Engineers form the execution spine of our Reinvention Deployment Engineering pods. We are building the largest FDE capability in the services industry. The engineers who join at this stage will define what the role looks like at scale and will have access to the hardest enterprise AI problems in the market across every industry.

Key Responsibilities

• Embed directly with client engineering and business teams to deploy, scale, and operationalize AI platforms - Anthropic, OpenAI, Microsoft, Google, Salesforce, SAP, or Palantir - inside enterprise environments
• Own production outcomes end-to-end: time-to-value, reliability, adoption velocity, and scalability, with business metrics attached - not just delivery milestones
• Move from ambiguous business problem to working production system through rapid experimentation: days to prototype, 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 client CTO, CFO, and CISO; shape use case roadmaps, ROI backlogs, and AI adoption strategy
• Build reusable patterns, playbooks, and accelerators that the client owns after you leave - enabling the client team to run it without you
• Lead design workshops, proofs of concept, architecture walkthroughs, and code-with sessions with client engineering and leadership teams
• Codify patterns and delivery learnings that scale across engagements and contribute to the growth of the FDE practice

Job Qualifications

• 3-5 years engineering experience with cloud-native systems (APIs, microservices, containerization, serverless).
• Minimum of 1 years of deep expertise in designing and deploying agentic solutions (agents, orchestration, context engineering, RAG, workflows) in production environments.
• Minimum of 3 years of experience with AI platforms - OpenAI, Claude, Vertex AI, plus open-source models - including building abstraction layers to manage multi-provider pipelines.
• Minimum of 10 years of experience deploying to production , CI/CD, infrastructure as code (Terraform, Helm), 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
• Proven ability to articulate business value: can quantify the impact of deployments in terms a CFO would recognize and act on
• Experience presenting to and building trust with senior client stakeholders, CTO, CFO, or CISO level
• Non-linear profiles are expected and welcomed, assessment is based on demonstrated deployment experience and outcome ownership, not CV pattern matching