Head of Production AI Engineering

Accenture Infrastructure and Capital Projects, LLC

Newcastle upon Tyne

On-site

GBP 120,000 - 180,000

Full time

14 days+
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Job summary

Accenture is seeking an AI Engineer (Agentic/Applied) to design, build, and deploy production-grade agentic AI solutions across the full enterprise tech stack. You will work with client engineering teams, lead technical design sessions, and develop reusable accelerators to scale across engagements.

You will own LLMOps, define evaluation and observability standards, and drive architecture discussions with senior stakeholders. Strong Python and cloud-native experience are required.

Qualifications

  • Experience shipping production-grade agentic AI solutions.
  • Hands-on experience calling LLM APIs in production code.
  • Proficient in cloud-native engineering (Kubernetes, microservices, CI/CD).
  • Strong Python and at least one backend language (Java or equivalent).

Responsibilities

  • Architect and govern production-grade agentic solutions at enterprise scale across environments.
  • Define RAG pipeline standards and embedding strategies.
  • Own LLMOps, evaluation strategies, and observability tooling.
  • Lead client engineering engagements at senior level and drive architecture sessions.
  • Publish reusable patterns and engineering standards across engagements.
  • Define program-level AI impact in business terms to stakeholders.

Skills

Python programming
Architectural design
Production debugging
Client engagements
Team leadership

Tools

Kubernetes
Docker
Terraform
LangGraph
CrewAI
AutoGen

Job description

Accenture is seeking an AI Engineer (Agentic/Applied) to design, build, and deploy production-grade agentic AI solutions across the full enterprise tech stack. You will work with client engineering teams, lead technical design sessions, and develop reusable accelerators to scale across engagements.

You will own LLMOps, define evaluation and observability standards, and drive architecture discussions with senior stakeholders. Strong Python and cloud-native experience are required.

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