Forward Deployed Engineer

Accenture UK & Ireland; Greater London; On-site; GBP 90,000 - 130,000; Full time

Job summary

Accenture UK & Ireland is seeking a Forward Deployed AI Engineer who will embed with client teams to deploy production AI platforms, driving time-to-value, reliability, adoption, and scalability in real enterprise environments.

You will design and govern AI architectures across identity, data, and security, translate technical capabilities into business impact for executives, and build reusable patterns and accelerators for client use after go-live.

Qualifications

• Cloud-native engineering experience (APIs, microservices, containerization, serverless).
• Deep expertise in agentic deployments (agents, orchestration, context engineering, RAG, workflows).
• Experience with AI platforms — OpenAI, Claude, Vertex AI, plus open-source models.
• Experience deploying to production, CI/CD, infrastructure as code (Terraform, Helm).
• Demonstrated end-to-end delivery ownership in a client-embedded environment.
• Proven ability to articulate business value to executives (e.g., CFO).
• Experience presenting to senior client stakeholders (CTO, CFO, CISO).
• Non-linear profiles welcomed; deployment experience and outcome ownership valued.

Responsibilities

• Embed with client engineering and business teams to deploy, scale, and operationalize AI platforms.
• Own production outcomes end-to-end: time-to-value, reliability, adoption velocity, and scalability with business metrics.
• Move from ambiguous business problem to working production system via rapid prototyping.
• Design and govern AI architectures across the full enterprise stack: identity, data, security, workflow integration.
• Translate technical architecture into business impact for client CTO, CFO, and CISO; shape roadmaps and ROI backlogs.
• Build reusable patterns, playbooks, and accelerators that clients own after you leave.
• Lead design workshops, proofs of concept, architecture reviews with client teams.
• Codify patterns and delivery learnings to scale across engagements and grow the FDE practice.

Skills

Cloud-native engineering

Agentic AI deployments

AI platforms

CI/CD & IaC

Delivery ownership

Business value articulation

Stakeholder management

Tools

Terraform

Helm

Job description

Role Description This is not a consulting role. It is not a project delivery role. It is not a research position. A Forward Deployed AI Engineer is a production engineer who works embedded inside a client's enterprise, shoulder to shoulder with their teams, to make complex AI platforms work in real, messy organizational environments. You own outcomes: time-to-value, adoption, reliability, and scalability. Not delivery milestones. Outcomes. 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

Basic Qualifications

• Engineering experience with cloud-native systems (APIs, microservices, containerization, serverless).
• Deep expertise in designing and deploying agentic solutions (agents, orchestration, context engineering, RAG, workflows) in production environments.
• Experience with AI platforms — OpenAI, Claude, Vertex AI, plus open-source models — including building abstraction layers to manage multi-provider pipelines.
• 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