About this role
Salary: £61,000 - 101,000 per year
Requirements: We require extensive software engineering experience in production environments.We require hands-on experience designing and deploying agentic AI solutions in a production environment.We require demonstrated experience with agentic orchestration frameworks such as LangGraph, CrewAI, AutoGen, or equivalent at production depth.We require direct experience calling LLM APIs such as OpenAI, Anthropic, and Vertex AI in production code, including provider abstraction, token management, and latency/cost tradeoffs.We require RAG pipeline ownership, including embeddings, chunking strategy, vector databases, and context engineering.We require LLMOps fundamentals, including eval harness design, prompt versioning, and production observability.We require cloud-native engineering maturity with Kubernetes, Docker, microservices, serverless, CI/CD, and IaC such as Terraform or Helm.We require strong Python skills; Java or an equivalent backend language is acceptable.We require production debugging and observability experience.We require people leadership experience, including managing, developing, and performance-managing engineers, setting development plans, and conducting career conversations. Responsibilities: We design, build, and deploy production-grade agentic AI systems across the full enterprise technology stack.We 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.We define RAG pipeline standards across engagements, including chunking and embedding strategies, quality benchmarks, and metric-backed tradeoff decisions.We set multi-LLM integration standards with vendor-agnostic architecture, fallback routing, and cost governance across providers including OpenAI, Anthropic, Vertex AI, and open-source models.We own LLMOps at programme scale, including eval strategy, prompt governance, observability tooling standards, safety monitoring, and cost controls across multiple concurrent systems.We lead client engineering engagements at a senior level, facilitate architecture design sessions, lead proof-of-concept delivery, and drive alignment between client technology leadership and delivery teams.We shape and publish reusable patterns, accelerators, and engineering standards that scale across our practice and reduce ramp-up time on new client engagements.We own the measurement framework for agentic system quality, defining accuracy, latency, safety, and cost metrics and presenting programme-level AI impact in business terms to senior client stakeholders. Technologies: Agentic AIAIArchitectBackendCI/CDCloudDockerHelmJavaKubernetesLLMPythonRAGServerlessTerraformmicroservices More:
hackajob is partnering directly with Accenture to hire for this role. We build production agentic architectures inside real client organizations and work across every industry, enterprise technology stack, and level of organizational complexity. We offer vendor fellowship access inside Anthropic, OpenAI, Microsoft, and Google engineering teams, plus a direct pathway to the Forward Deployed Engineer programme. Accenture is a leading global professional services company with approximately 791,000 people serving clients in more than 120 countries. We help leading businesses, governments, and other organizations build their digital core, optimize operations, accelerate revenue growth, and enhance citizen services. Our broader services span Strategy & Consulting, Technology, Operations, Industry X, and Song, supported by strong cloud, data, and AI capabilities, global delivery, and a culture of shared success and 360 value. We are committed to inclusion and equal opportunity, and our diverse workforce helps us better serve our clients and communities.
last updated 39 week of 2026