Forward Deployed Engineer

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

Job summary

Accenture is seeking an experienced Forward Deployed AI Engineer to embed with client teams in London, delivering AI platforms at enterprise scale.

You will own outcomes from prototype to production, defining architectures, governance, and scalable patterns while collaborating across business and technical stakeholders.

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

• Embed directly with client engineering and business teams to deploy, scale, and operationalise AI platforms, including Anthropic, OpenAI, Microsoft, Google, Salesforce, SAP, and Palantir, inside enterprise environments
• Own production outcomes end-to-end: time-to-value, reliability, adoption velocity, and scalability
• 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, spanning identity, data, security, governance, platform layer, and workflow integration
• Build reusable patterns, playbooks, and accelerators that the client owns after you leave, and codify delivery learnings that scale across engagements

Skills

Cloud-native

APIs

Microservices

Containerization

Serverless

Agentic solutions

Context engineering

RAG

Workflows

OpenAI

Claude

Vertex AI

Open-source models

Leadership

Delivery ownership

Tools

OpenAI

Claude

Vertex AI

Open-source models

Job description

Job Description

Shape the future of AI-led business transformation.

A Forward Deployed AI Engineer works embedded inside a client's enterprise, shoulder to shoulder with their teams, making complex AI platforms work in realorganisational environments. You own outcomes: time-to-value, adoption, reliability, and scalability.

We are building the largest Forward Deployed Engineering capability in the services industry. The engineers who join at this stage will define what the role looks like atscale, andwill work on themost interesting enterprise AI problems across every industry.

What you will do

• Embed directly with client engineering and business teams to deploy, scale, and operationalise AI platforms, including Anthropic, OpenAI, Microsoft, Google, Salesforce, SAP, and Palantir, inside enterprise environments
• Own production outcomes end-to-end: time-to-value, reliability, adoption velocity, and scalability
• 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, spanning identity, data, security, governance, platform layer, and workflow integration
• Build reusable patterns, playbooks, and accelerators that the client owns after you leave, and codify delivery learnings that scale across engagements

Qualification

Basic Qualifications

• Engineering experience with cloud-native systems (APIs, microservices, containerization, serverless).
• Deepexpertisein 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,allocatingresources 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 ondemonstrateddeployment 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

# LI-MP

Locations

London

Equal Employment Opportunity Statement

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About Accenture

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