Enterprise AI Deployment Architect

Accenture UK

Newcastle upon Tyne

On-site

GBP 90,000 - 130,000

Full time

14 days+

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Job summary

Accenture is seeking a Forward Deployed AI Engineer to join our Reinvention Deployment Engineering practice. You will operate inside client environments, owning time-to-value, adoption, reliability, and scalability of AI platforms.

You will translate platform capabilities into measurable business outcomes, leading complex deployments across diverse enterprise settings. You will drive multi-stakeholder programs, shape AI reinvention strategies for CTO/CFO/CISO audiences, and publish reusable

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 leading software engineering teams: overseeing delivery, allocating resources across workstreams, and owning the professional development of direct reports.
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
People lead responsibilities: experience managing, developing, and performance-managing a team of engineers; setting individual development plans and conducting career conversations

Responsibilities

Lead enterprise AI platform deployments across complex multi-stakeholder client environments — Anthropic, OpenAI, Microsoft, Google, Salesforce, SAP, or Palantir — owning the full programme from architecture through adoption
Own programme-level delivery outcomes: time-to-value, reliability, adoption velocity, and scalability across multiple concurrent workstreams, with commercial metrics attached
Lead rapid experimentation at pace: drive ambiguous business problems to working production systems in days or weeks across complex enterprise environments
Architect and govern enterprise AI solutions across the full technology stack: identity, data, security, governance, platform layer, and multi-system workflow integration at programme scale
Shape AI reinvention strategy for client CTO, CFO, and CISO: build value architecture, ROI backlogs, use case prioritisation frameworks, and multi-year AI adoption roadmaps
Define and publish reusable reinvention blueprints, patterns, and accelerators that scale across multiple client engagements and grow the FDE practice
Lead architecture design sessions, executive workshops, and code-with sessions with client engineering and C-suite leadership teams
Codify delivery learnings, failure patterns, and engineering standards that shape the FDE practice and enable the next generation of forward deployed engineers