The Job

AI Native Software Engineer

Technology, Data & Digital · Software & Web Development · Software Engineering

Join for updates

In short

Accenture is seeking an experienced AI Native Software Engineer in Newcastle to design, build, and deploy production-grade agentic AI solutions. This full-time role involves working with clients to implement complex AI architectures, own RAG pipelines, and manage LLMOps in enterprise environments.

Responsibilities

  • Design and build production-grade agentic solutions end-to-end, including multi-agent orchestration, RAG pipelines, policy-based routing, tool invocation, memory management, and lifecycle observability.
  • Build and own RAG pipelines, focusing on embeddings, chunking strategy, vector search, context window engineering, and tuning against real quality targets.
  • Integrate and abstract across multiple LLM providers (OpenAI, Anthropic, Vertex AI, open-source models) with fallback routing, token, cost, and latency management.
  • Implement LLMOps in production, including eval harnesses with real quality metrics, prompt versioning, observability tooling (LangSmith, Braintrust, or equivalent), and cost and safety monitoring.
  • Embed directly with client engineering teams to analyze the SDLC, identify AI/agentic opportunities, and deploy solutions through workshops, proofs of concept, code-with sessions, and architecture walkthroughs.
  • Build reusable patterns, accelerators, and playbooks that scale beyond individual client engagements.
  • Define and use metrics to measure agent accuracy, latency, safety, and cost-effectiveness, and present findings to client stakeholders in business terms.

Requirements

  • Significant software engineering experience in production environments.
  • Hands-on experience designing and deploying agentic AI solutions in a production environment – non-negotiable.
  • Demonstrated experience with agentic orchestration frameworks like LangGraph, CrewAI, AutoGen, or equivalent at production depth.
  • Direct experience calling LLM APIs (OpenAI, Anthropic, Vertex AI) in production code, including provider abstraction, token management, and latency/cost tradeoffs.
  • RAG pipeline ownership: embeddings, chunking strategy, vector databases, and context engineering.
  • LLMOps fundamentals: eval harness design, prompt versioning, and production observability.
  • Cloud-native engineering maturity: Kubernetes, Docker, microservices, serverless, CI/CD, and IaC (Terraform or Helm).
  • Strong Python; Java or equivalent backend language acceptable; production debugging and observability experience.
  • Quality of experience is weighted over years; a candidate who has shipped three production agentic systems in four years is preferred over a generalist with passive AI exposure.

Benefits

  • Breadth across every industry, every enterprise technology stack, and every level of organizational complexity.
  • Vendor fellowship access inside Anthropic, OpenAI, Microsoft, and Google engineering teams.
  • Direct pathway to the Forward Deployed Engineer programme.
  • Opportunities to keep skills relevant through certifications, learning, and diverse work experiences.
  • Support for people’s physical, mental, and financial health.
  • Consistently recognized as one of the World’s Best Workplaces™.
#AI#Software Engineering#Agentic AI#LLMOps#RAG
Accenture Logo

Company

Accenture

Job Posted

1 week ago

Employment Type

Full Time

WorkMode

On Site

Experience Level

Mid-Senior

Locations

Newcastle, United Kingdom

Applicants

Be an early applicant