Forward Deployed Engineer

Accenture; Greater London; On-site; GBP 120,000 - 180,000; Full time

Job summary

Accenture is hiring Forward Deployed AI Engineers in the UK. You will embed with client teams to deploy and scale AI platforms, owning outcomes from time-to-value to reliability. You will design enterprise AI architectures and translate technical work into measurable business impact for client CTOs, CFOs, and CISOs.

You will work within Reinvention Deployment Engineering pods to tackle complex, real-world AI problems across industries, driving scalable, reusable patterns for client success.

Qualifications

• Engineering experience with cloud-native systems (APIs, microservices, containerization, serverless).
• Experience designing and deploying agentic solutions (agents, orchestration, context engineering, RAG, workflows) in production environments.
• Strong experience with AI platforms — OpenAI, Claude, Vertex AI, plus open-source models — including abstraction layers to manage multi-provider pipelines.
• Very strong experience deploying to production, CI/CD, infrastructure as code (Terraform, Helm), monitoring, and debugging.
• Proven ability to articulate business value to C-suite and translate deployments into measurable outcomes.

Responsibilities

• Embed with client teams to deploy, scale, and operationalize AI platforms inside enterprise environments.
• Own production outcomes end-to-end: time-to-value, reliability, adoption velocity, scalability with business metrics.
• Move from ambiguous problems to production-ready systems via rapid prototyping and iteration.
• Design and govern AI architectures across identity, data, security, governance, and workflow integration.
• Translate technical architecture into client business impact and shape AI adoption roadmaps.

Skills

Cloud-native architectures

Agentic solutions design

AI platforms deployment

CI/CD & IaC

Production deployment ownership

Stakeholder communication

Architectural governance

Reliability & scalability

Job description

Accenture is a leading global professional services company, providing a broad range of services in strategy and consulting, interactive, technology and operations, with digital capabilities across all of these services. With our thought leadership and culture of innovation, we apply industry expertise, diverse skill sets and next-generation technology to each business challenge.

We believe in inclusion and diversity and supporting the whole person. Our core values comprise of Stewardship, Best People, Client Value Creation, One Global Network, Respect for the Individual and Integrity. Year after year, Accenture is recognized worldwide not just for business performance but for inclusion and diversity too.

"Across the globe, one thing is universally true of the people of Accenture: We care deeply about what we do and the impact we have with our clients and with the communities in which we work and live. It is personal to all of us." – Julie Sweet, Accenture CEO

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).
• Some expertise in designing and deploying agentic solutions (agents, orchestration, context engineering, RAG, workflows) in production environments.
• Strong experience with AI platforms — OpenAI, Claude, Vertex AI, plus open-source models — including building abstraction layers to manage multi-provider pipelines.
• Very strong 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