Accenture UK & Ireland
Forward Deployed Engineering Specialist
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Forward Deployed Engineering Specialist
Senior Forward Deployed AI Engineer
We are looking for a Forward Deployed AI Engineer / Production Engineer who will embed inside a client’s enterprise shoulder to shoulder with their teams. Your role is to make complex AI platforms work in real-world, messy organizational environments. You will own measurable business outcomes: time-to-value, adoption, reliability, and scalability—not just delivery milestones.
Why This Role Matters
The market understands what leading tech companies have proven: AI products fail not because the models are weak, but because deployment is broken. The gap between a successful AI pilot and a scalable AI capability is bridged by engineers who can translate technical capability into business value within the complexities of an enterprise.
Forward Deployed AI Engineers form the execution core of our Reinvention Deployment Engineering pods. This is the role that will define the future of FDE at scale, tackling the hardest AI challenges across every industry, with elite access to the market’s toughest problems.
Responsibilities
- Embed directly with client engineering and business teams to deploy, scale, and operationalize AI platforms (e.g., Anthropic, OpenAI, Microsoft, Google, Salesforce, SAP, Palantir) inside real-world environments
- Own production outcomes end-to-end, including:
- Time-to-value
- Reliability
- Adoption velocity
- Scalability
- Business metrics (not just delivery deliverables)
- Rapidly move from vague business problems to production systems: prototype in days, deploy in weeks
- Design and govern AI architectures across the full enterprise stack, including:
- Identity & access
- Data strategy
- Security & governance
- Platform layers
- Workflow integration
- Translate technical architectures into business impact, advising CTOs, CFOs, and CISOs, shaping:
- Use-case roadmaps
- ROI backlogs
- AI adoption strategy
- Build reusable patterns, playbooks, and accelerators that the client can own after you leave, ensuring long-term sustainability
- Lead critical client engagement tasks, including:
- Design workshops
- Proofs-of-concept
- Architecture reviews
- Code-with sessions (select to client teams and leadership)
- Codify patterns and learnings to scale across multiple engagements, contributing to the growth of the FDE practice
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Qualifications & Requirements
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- Engineering experience in cloud-native systems: APIs, microservices, containerization, serverless
- Expertise in designing, deploying, and managing agentic solutions in production:
- AI agents, orchestration, context engineering, RAG (Retrieval-Augmented Generation)
- Enterprise workflows that integrate with AI models
- Hands-on experience with major AI platforms:
- OpenAI, Anthropic, Vertex AI, Claude, and open-source models
- Abstraction layers to manage multi-provider AI pipelines
- Strong production deployment expertise:
- CI/CD pipelines
- Infrastructure as Code (Terraform, Helm)
- Monitoring, observability, and debugging
- Proven track record of end-to-end accountability in client-embedded engagements (internal or vendor projects do not count)
- Ability to articulate business ROI at executive level:
- Quantify AI impact for CFOs, CTOs, and CISOs
- Build trust with senior leadership
- Non-linear, hands-on profiles encouraged: Selection based on evidence of deployment experience—not just traditional CV fit
(Note: Other responsibilities and details shall carry equal weight as above, as per the provided content.)
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