Forward Deployed Engineer Specialist

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.

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   Commercial experience with cloud-native systems (APIs, microservices, containerization, serverless).  Experience of deep expertise in designing and deploying agentic solutions (agents, orchestration, context engineering, RAG, workflows) in production environments.  Commercial experience with AI platforms — OpenAI, Claude, Vertex AI, plus open-source models — including building abstraction layers to manage multi-provider pipelines.  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  #LI-MP About Accenture Accenture is a leading global professional services company that helps the world’s leading businesses, governments and other organizations build their digital core, optimize their operations, accelerate revenue growth and enhance citizen services—creating tangible value at speed and scale. We are a talent- and innovation-led company with approximately 791,000 people serving clients