The Job

AI Software Engineering Manager

Teknik, data och digitalt · Mjukvaru- och webbutveckling · Mjukvaruutveckling

Gå med för uppdateringar

I korthet

As an AI Software Engineering Manager, you will architect and deploy production-grade agentic AI solutions at enterprise scale, including multi-agent orchestration, RAG pipelines, and LLMOps. You will lead client engagements, define standards for LLM integration and RAG pipelines, and manage a team of engineers, focusing on quality and production readiness.

Ansvarsområden

  • Architect and govern production-grade agentic solutions at enterprise scale: multi-agent orchestration, RAG pipelines, policy-based routing, memory management, and programme-level lifecycle observability
  • Define RAG pipeline standards across engagements: establish chunking and embedding strategies, set quality benchmarks, and ensure metric-backed tradeoff decisions are documented and transferable
  • Set multi-LLM integration standards: vendor-agnostic architecture by default, fallback routing and cost governance across providers including OpenAI, Anthropic, Vertex AI, and open-source models
  • Own LLMOps at programme scale: evaluation strategy, prompt governance, observability tooling standards, safety monitoring and cost controls
  • Lead client engineering engagements at senior level — analyse SDLC, identify AI/agentic opportunities, facilitate design sessions, lead proof-of-concept delivery, and drive alignment
  • Shape and publish reusable patterns, accelerators, and engineering standards
  • Own the measurement framework for agentic system quality: define accuracy, latency, safety, and cost metrics; present programme-level AI impact in business terms

Krav

  • Extensive software engineering experience in production environments
  • Hands-on experience designing and deploying agentic AI solutions in a production environment — non-negotiable
  • Demonstrated experience with agentic orchestration frameworks: LangGraph, CrewAI, AutoGen, or equivalent — at production depth
  • Direct experience calling LLM APIs (OpenAI, Anthropic, Vertex AI) in production code: provider abstraction, token management, latency and cost tradeoffs
  • RAG pipeline ownership: embeddings, chunking strategy, vector databases, and context engineering
  • LLMOps fundamentals: eval harness design, prompt versioning, and production observability
  • Cloud-native engineering maturity: Kubernetes, Docker, microservices, serverless, CI/CD, and IaC (Terraform or Helm)
  • Strong Python; Java or equivalent backend language acceptable; production debugging and observability experience
  • People lead responsibilities: experience managing, developing, and performance-managing a team of engineers; setting individual development plans and conducting career conversations

Önskade kvalifikationer

  • Quality of experience is weighted over years, a candidate who has shipped three production agentic systems in four years is preferred over a generalist with passive AI exposure

Förmåner

  • Breadth across every industry, every enterprise technology stack, and every level of organizational complexity
  • Vendor fellowship access inside Anthropic, OpenAI, Microsoft, and Google engineering teams
  • Direct pathway to the Forward Deployed Engineer programme
  • Opportunities to keep skills relevant through certifications, learning, and diverse work experiences
  • Consistently recognized as one of the World’s Best Workplaces™
#AI#Software Engineering#Agentic AI#Production#Enterprise#LLM#RAG#LLMOps#Cloud#Python#Java#Kubernetes#Docker#CI/CD#IaC#Team Lead
Accenture Logo

Företag

Accenture

Publicerade jobb

för 4 veckor sedan

Anställningstyp

Heltid

Arbetsform

På plats

Erfarenhetsnivå

Senior

Platser

Newcastle, United Kingdom

Sökande

Ansök tidigt