AI Native SW Eng

Salary: £61,000 - 101,000 per year Requirements: • Extensive software engineering experience in production environments • Hands-on experience designing and deploying agentic AI solutions in a production environment • Demonstrated experience with agentic orchestration frameworks such as LangGraph, CrewAI, AutoGen, or equivalent at production depth • Direct experience calling LLM APIs such as OpenAI, Anthropic, or Vertex AI in production code, including provider abstraction, token management, latency, and cost tradeoffs • RAG pipeline ownership, including embeddings, chunking strategy, vector databases, and context engineering • LLMOps fundamentals, including eval harness design, prompt versioning, and production observability • Cloud-native engineering maturity with Kubernetes, Docker, microservices, serverless, CI/CD, and IaC such as Terraform or Helm • Strong Python skills; Java or an equivalent backend language is acceptable • Production debugging and observability experience • People leadership experience, including managing, developing, and performance-managing a team of engineers, setting individual development plans, and conducting career conversations Responsibilities: • Architect and govern production-grade agentic systems at enterprise scale, including multi-agent orchestration, RAG pipelines, policy-based routing, memory management, and programme-level lifecycle observability • Define RAG pipeline standards across engagements, including chunking and embedding strategies, quality benchmarks, and metric-backed tradeoff decisions • Set multi-LLM integration standards with vendor-agnostic architecture, fallback routing, and cost governance across providers • Own LLMOps at programme scale, including eval strategy, prompt governance, observability tooling standards, safety monitoring, and cost controls across multiple concurrent systems • Lead client engineering engagements at a senior level, facilitate architecture design sessions, lead proof-of-concept delivery, and align client technology leadership with delivery teams • Shape and publish reusable patterns, accelerators, and engineering standards that scale across the practice and reduce ramp-up time on new client engagements • Own the measurement framework for agentic system quality by defining accuracy, latency, safety, and cost metrics and presenting programme-level AI impact in business terms to senior client stakeholders Technologies: • Agentic AI • AI • Architect • Backend • CI/CD • Cloud • Docker • Helm • Java • Kubernetes • LLM • Python • RAG • Serverless • Terraform • microservices More: We are partnering directly with Accenture to hire for this role. We build production-grade agentic AI systems for enterprise environments, working directly with client engineering teams and across the full enterprise technology stack. We offer breadth across industries and enterprise complexity, along with vendor fellowship access inside Anthropic, OpenAI, Microsoft, and Google engineering teams and a direct pathway to the Forward Deployed Engineer programme. Accenture is a leading global professional services company serving clients in more than 120 countries, with technology at the core of its work and strong capabilities across cloud, data, AI, and global delivery. We are a talent- and innovation-led company committed to creating 360 value for our clients, each other, our shareholders, partners, and communities. last updated 38 week of 2026