You and the process

With a person
Anna, in-house recruiter
9 years hiring engineers
30 minutes with a real recruiter
They read your CV with you, on a call, and say where the offers are being lost.
Didn’t find what you were looking for? Tell us what to build
Accenture

AI Native Software Engineer

  • Office
  • 3-6 years

Salary

Not stated

Similar roles pay £90K - 130K a year · our estimate

AI summary

For members

The whole posting in a few lines. Sign up to read it here and on every role you open.

Sign Up to Read

Description

Please Note: Any offer of employment is subject to satisfactory BPSS and SC security clearance which typically requires 5 years continuous UK address history usually including no periods of 30 consecutive days or more spent outside of the UK.

Note: The above information relates to a specific client requirement

You build the solutions that actually make AI work in enterprise environments, not demos, not prototypes that stall after a pilot, but production agentic architectures running inside real client organizations. The difference between an AI Engineer and what we are looking for is straightforward: you have shipped a multi-agent solution in production, you have owned the eval uation harness, and you know what happens when your agent fails at 2am because you have lived it.

As an AI Engineer (Agentic/Applied), you will design, build, and deploy production-grade agentic AI solutions across the full enterprise technology stack. You will work directly with client engineering teams, lead technical design sessions, and build reusable patterns and accelerators that scale beyond individual engagements to maximise efficiencies across the software delivery lifecycle .

This role sits at the heart of the AI engineering talent market — demand is growing faster than supply and will continue to do so. We offer what no single product company can: breadth across every industry, every enterprise technology stack, and every level of organizational complexity, combined with vendor fellowship access inside Anthropic, OpenAI, Microsoft, and Google engineering teams and a direct pathway to the Forward Deployed Engineer programme.

Responsibilities

  • Design and build production-grade agentic solutions end-to-end: multi-agent orchestration, RAG pipelines, policy-based routing, tool invocation, memory management, and lifecycle observability
  • Build and own RAG pipelines: 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, and open-source models — with fallback routing, token, cost, and latency management
  • Implement LLMOps in production: eval harnesses with real quality metrics, prompt versioning, observability tooling (LangSmith, Braintrust, or equivalent), cost and safety monitoring
  • Embed directly with client engineering teams to analyse the SDLC to identify AI/agentic opportunities and use cases, design, prototype, and deploy agentic solutions — workshops, proofs of concept, code-with sessions, and architecture walkthroughs
  • Build reusable patterns, accelerators, and playbooks that scale beyond the individual client engagement and enable the next one to start faster
  • Define and use metrics to measure agent accuracy, latency, safety, and cost-effectiveness; present findings and recommendations to client stakeholders in business terms
  • 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: LangGraph, CrewAI, AutoGen, or equivalent — at production depth, not tutorial level
  • Direct experience calling LLM APIs (OpenAI, Anthropic, Vertex AI) in production code: provider abstraction, token management, latency and 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
  • LI-EU
  • About Accenture
  • Accenture is a leading global professional services company that helps the world’s leading businesses, governments and other organizations build their digital core, optimize their operations, accelerate revenue growth and enhance citizen services—creating tangible value at speed and scale. We are a talent- and innovation-led company with approximately 791,000 people serving clients in more than 120 countries. Technology is at the core of change today, and we are one of the world’s leaders in helping drive that change, with strong ecosystem relationships. We combine our strength in technology and leadership in cloud, data and AI with unmatched industry experience, functional expertise and global delivery capability. Our broad range of services, solutions and assets across Strategy & Consulting, Technology, Operations, Industry X and Song, together with our culture of shared success and commitment to creating 360° value, enable us to help our clients reinvent and build trusted, lasting relationships. We measure our success by the 360° value we create for our clients, each other, our shareholders, partners and communities.
  • Visit us at www.accenture.com

Where you’d work

From the office

About the company

Accenture

Office in United Kingdom

Also hiring in Melbourne, Australia, Australia, France and 70 more places

4 of their 92 open roles are remote

Your chances

Worth a look before you spend an evening tailoring a CV for it.

  • 19 checks run
  • 1 red flag

Still hiring?

13 checks

No red flags

How crowded?

6 checks

1 red flag

Fits Me

How well does this role fit you?

Answer a few questions or drop your CV, and every role gets a fit score with the reasons, this one first.

  • Your field
  • Level
  • Stack
  • Work model
  • Salary floor
  • Must-haves
Details10 facts · Role, Location, Compensation, Employment
Tech stack
  • Python
  • Java
  • Kubernetes
  • Docker
  • Terraform
  • CI/CD
  • LLMs
  • RAG
  • LangChain
  • Vector databases
Type
Full-time
Specialty
Backend
Region
United Kingdom
Pay period
Annual
Show 5 more factsShow less

Role

Category
Development
Specialty
Backend
Experience
5+ years
Tech stack
  • Python
  • Java
  • Kubernetes
  • Docker
  • Terraform
  • CI/CD
  • LLMs
  • RAG
  • LangChain
  • Vector databases

Location

Work model
Office
Region
United Kingdom
Office
  • United Kingdom

Compensation

Salary
Salary by agreement
Pay period
Annual

Employment

Type
Full-time

Something wrong with this vacancy?

Similar vacancies

Share this vacancy

What's wrong with it?

The employer never sees who reported.

Reason