AI Engineer, London, UK

AI Engineer, London, UK

United Kingdom | 05/14/2026

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Job Code : JPC - 68593

Job Description

Job Title: AI Engineer

Location : London, UK

Complete address: 30 Fenchurch Street (Plantation Place), London, EC3M 3BD, United Kingdom

Hybrid/Onsite : Hybrid - 3 days per week to office

Travel Required : Yes (To USA, 1 week in a quarter)

Contract Type: 40 hours per week

Duration: 12 months with extensions

Start Date : 26th May 2026

Client : Accenture

Years of Experience : 8-10 Years

Invoice to Apex : 100 USD per hour.

Job Description:

Overview:

Seeking a hands-on AI Native Software Engineer to design, build, and deploy production-grade AI-driven systems within enterprise environments. The role focuseson implementing agent-based workflows, integrating AI platforms, and delivering scalable cloud-native solutions.

Required Skills & Experience

Must be able and willing to travel 80-90% of the time to various customer sites

Must be authorized to work in the U.S. without requiring sponsorship

8-10+ years of software engineering experience

Strong experience with cloud-native systems (APIs, microservices, containers, serverless)

Experience building and deploying AI/LLM-based systems in production (agents, RAG, orchestration)

Proficiency in Python, Java, or similar backend languages

Experience with:

CI/CD pipelines

Infrastructure as code

Monitoring and observability tools

Hands-on experience with AI platforms (OpenAI, Claude, Vertex AI, or similar)

Preferred Experience

Experience with agent frameworks (e.g., LangGraph, AutoGen, CrewAI)

Experience designing multi-agent or distributed AI systems

Familiarity with enterprise-scale system integration

Experience optimizing AI workloads for cost and performance

Responsibilities

AI Agent Engineering

Design and implement AI agents, including:

Retrieval (RAG)

Orchestration workflows

Tool/function invocation

Policy-based routing

Build evaluation frameworks for accuracy, latency, and reliability

Implement observability and monitoring for agent lifecycle

AI Platform Integration

Integrate with AI providers (e.g., OpenAI, Anthropic, Google Vertex, open-source models)

Build abstraction layers to support multi-model and multi-provider architectures

Optimize model usage for performance, cost, and latency

Cloud-Native Development

Develop scalable services using:

Microservices architecture

Containers (Docker, Kubernetes)

Serverless and event-driven patterns

Implement CI/CD pipelines and infrastructure as code (e.g., Terraform, Helm)

Ensure production readiness, logging, monitoring, and fault tolerance

Application Development

Build and deploy AI-powered applications aligned to business workflows

Integrate AI systems into existing enterprise platforms and APIs

Develop backend services and APIs supporting agent workflows

Testing & Performance

Define and execute test strategies for AI systems

Measure system performance (latency, throughput, accuracy, cost)

Debug and optimize production systems

Scope & Expectations

100% hands-on engineering role (no people management)

Deliver production-quality code and deployments

Work within existing architecture and engineering standards

Collaborate with client and internal engineering teams as needed

Participate in technical design discussions (implementation-focused)