Forward Deployed Engineer

Accenture UK & Ireland

Greater London

Vor Ort

GBP 90.000 - 140.000

Vollzeit

vor 15 Stunden
Sei unter den ersten Bewerbenden
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Zusammenfassung

Accenture UK & Ireland seeks a Forward Deployed AI Engineer embedded with enterprise teams to deploy AI platforms at scale, ensuring time-to-value, adoption, reliability and security.

You will partner with client engineers to transform ambiguous problems into production systems, design architectures across data, identity, and governance, and create reusable patterns that endure beyond the engagement.

Qualifikationen

  • 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.
  • 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

Aufgaben

  • Embed directly with client engineering and business teams to deploy, scale, and operationalise AI platforms 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

Kenntnisse

Cloud-native systems
Agentic solutions design
AI platforms (OpenAI, Claude, Vertex)
Lead software engineering teams
End-to-end delivery ownership
Business value articulation
Stakeholder communication
Non-linear profiles welcomed

Tools

OpenAI
Claude
Vertex AI
Multi-provider pipelines

Jobbeschreibung

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 real organisational 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 at scale, and will work on the most 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
Basic 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
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