{"id":68849,"url":"https://alion.io/job/accenture-ai-software-engineering-specialist","title":"AI Native Software Engineer","company":{"id":271,"name":"Accenture","domain":"accenture.com","url":"https://alion.io/company/accenture","size_band":"5000+","is_staffing_agency":false,"employer_type":"services","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"A","score":100,"open_postings":2003,"ghost_share":0.001,"stale_share":0.086,"repost_share":0.005,"time_to_fill_p50_days":5,"computed_at":"2026-10-17T05:46:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Newcastle, United Kingdom"],"countries":["GB"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Anthropic","optional":false},{"name":"AutoGen","optional":false},{"name":"Braintrust","optional":false},{"name":"CI/CD","optional":false},{"name":"Context Engineering","optional":false},{"name":"CrewAI","optional":false},{"name":"Docker","optional":false},{"name":"Embeddings","optional":false},{"name":"Helm","optional":false},{"name":"Java","optional":false},{"name":"Kubernetes","optional":false},{"name":"LangGraph","optional":false},{"name":"LangSmith","optional":false},{"name":"LLM","optional":false},{"name":"LLM Evaluation","optional":false},{"name":"LLMOps","optional":false},{"name":"Multi-Agent Systems","optional":false},{"name":"OpenAI","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Terraform","optional":false},{"name":"Vertex AI","optional":false},{"name":"LangChain","optional":true}],"status":"live","first_seen_at":"2026-08-20T00:00:00Z","employer_posted_date":"2026-09-11","last_verified_at":"2026-10-17T13:33:40Z","board_verified":true,"closed_at":null,"days_open":58,"trust":{"level":"ok","repost_count":0,"flags":[],"days_open":58},"description":"Please Note: Any offer of employment is subject to satisfactory BPSS and SC security clearance which typically requires 5 years continuous UK address history usually including no periods of 30 consecutive days or more spent outside of the UK.\nNote: The above information relates to a specific client requirement\nYou build the solutionsthat actually make AI work in enterprise environments, not demos, not prototypes that stall after a pilot, but production agentic architectures running inside real client organizations. The difference between an AI Engineer and what we are looking for is straightforward: you have shipped a multi-agent solutionin production, you have owned the evaluationharness, and you know what happens when your agent fails at 2am because you have lived it.\nAs an AI Engineer (Agentic/Applied), you will design, build, and deploy production-grade agentic AI solutionsacross the full enterprise technology stack. You will work directly with client engineering teams, lead technical design sessions, and build reusable patterns and accelerators that scale beyond individual engagementsto maximise efficiencies across the software delivery lifecycle.\nThis role sits at the heart of the AI engineering talent market - demand is growing faster than supply and will continue to do so. We offer what no single product company can: breadth across every industry, every enterprise technology stack, and every level of organizational complexity, combined with vendor fellowship access inside Anthropic, OpenAI, Microsoft, and Google engineering teams and a direct pathway to the Forward Deployed Engineer programme.\nKey Responsibilities\nDesign and build production-grade agentic solutionsend-to-end: multi-agent orchestration, RAG pipelines, policy-based routing, tool invocation, memory management, and lifecycle observability\nBuild and own RAG pipelines: embeddings, chunking strategy, vector search, context window engineering and tuning against real quality targets\nIntegrate and abstract across multiple LLM providers - OpenAI, Anthropic, Vertex AI, and open-source models - with fallback routing, token, cost, and latency management\nImplement LLMOps in production: eval harnesses with real quality metrics, prompt versioning, observability tooling (LangSmith, Braintrust, or equivalent), cost and safety monitoring\nEmbed directly with client engineering teams to analyse the SDLC to identify AI/agentic opportunities and use cases,design, prototype, and deploy agentic solutions - workshops, proofs of concept, code-with sessions, and architecture walkthroughs\nBuild reusable patterns, accelerators, and playbooks that scale beyond the individual client engagement and enable the next one to start faster\nDefine and use metrics to measure agent accuracy, latency, safety, and cost-effectiveness; present findings and recommendations to client stakeholders in business terms\nSignificant software engineering experience in production environments\nHands-on experience designing and deploying agentic AI solutions in a production environment - non-negotiable\nDemonstrated experience with agentic orchestration frameworks: LangGraph, CrewAI, AutoGen, or equivalent - at production depth, not tutorial level\nDirect experience calling LLM APIs (OpenAI, Anthropic, Vertex AI) in production code: provider abstraction, token management, latency and cost tradeoffs\nRAG pipeline ownership: embeddings, chunking strategy, vector databases, and context engineering\nLLMOps fundamentals: eval harness design, prompt versioning, and production observability\nCloud-native engineering maturity: Kubernetes, Docker, microservices, serverless, CI/CD, and IaC (Terraform or Helm)\nStrong Python; Java or equivalent backend language acceptable; production debugging and observability experience\nQuality 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\n\nAbout Accenture\nAccenture is a leading global professional services company that helps the world’s leading businesses, governments and other organizations build their digital core, optimize their operations, accelerate revenue growth and enhance citizen services-creating tangible value at speed and scale. We are a talent- and innovation-led company with approximately 791,000 people serving clients in more than 120 countries. Technology is at the core of change today, and we are one of the world’s leaders in helping drive that change, with strong ecosystem relationships. We combine our strength in technology and leadership in cloud, data and AI with unmatched industry experience, functional expertise and global delivery capability. Our broad range of services, solutions and assets across Strategy & Consulting, Technology, Operations, Industry X and Song, together with our culture of shared success and commitment to creating 360° value, enable us to help our clients reinvent and build trusted, lasting relationships. We measure our success by the 360° value we create for our clients, each other, our shareholders, partners and communities.Visit us atwww.accenture.com\nEqual Employment Opportunity Statement\nWe believe that no one should be discriminated against because of their differences. All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, sexual orientation, gender identity or expression, marital status, citizenship status or any other basis as protected by applicable law. 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