AI Native Software Engineer — Production AI & Agentic Systems

Accenture; Birmingham; Hybrid; GBP 75,000 - 120,000; Full time

Job summary

Accenture is seeking AI Native Software Engineers to join the AI Engineering team in London & Birmingham, working across Agentic and Applied AI. We hire across levels, so scope and ownership depend on your background and depth.

You will design, build and deploy production-grade software and AI systems, turning AI capabilities into reliable real-world solutions that scale with real environments.

Qualifications

• Strong software engineering fundamentals in Python, Java or TypeScript.
• Experience with AI model integration and production deployment.
• Hands-on with agentic architectures and multi-agent systems.

Responsibilities

• Designing and deploying production-grade agentic and multi-agent systems.
• Building RAG pipelines, including embeddings, chunking, vector search and context engineering.
• Integrating LLM APIs across providers such as OpenAI, Anthropic, Vertex AI and open-source models.
• Building orchestration, tool invocation, routing and memory capabilities.
• Developing evaluation frameworks and measuring accuracy, latency, cost and safety.
• Implementing LLMOps practices including prompt versioning, observability and production monitoring.
• Building APIs, backend services and full-stack applications that connect software systems with AI and agentic backends.
• Designing and deploying cloud-native solutions using Docker, Kubernetes, CI/CD and infrastructure as code.
• Using AI-assisted development throughout the software delivery lifecycle, including coding, testing, debugging and code review.

Skills

Python

Java

TypeScript

Agentic frameworks

LLM APIs

Job description

Accenture is seeking AI Native Software Engineers to join the AI Engineering team in London & Birmingham, working across Agentic and Applied AI. We hire across levels, so scope and ownership depend on your background and depth.

You will design, build and deploy production-grade software and AI systems, turning AI capabilities into reliable real-world solutions that scale with real environments.