AI Engineer, London, UK

AI Engineer, London, UK United Kingdom | 05/14/2026 Easy Apply

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)