{"id":1799625,"url":"https://alion.io/job/capgemini-lead-ai-engineer","title":"Lead AI Engineer","company":{"id":145,"name":"Capgemini","domain":"capgemini.com","url":"https://alion.io/company/capgemini","size_band":"5000+","is_staffing_agency":false,"employer_type":"services","is_intermediary":false,"listed_via":null,"ats_vendor":"Career site","truth_index":{"grade":"B","score":75,"open_postings":915,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":23,"computed_at":"2026-10-05T05:45:15Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"lead","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Birmingham, United Kingdom"],"countries":["GB"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":84000,"max_usd":175000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":17},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agentic Workflows","optional":false},{"name":"AI Agents","optional":false},{"name":"Amazon SageMaker","optional":false},{"name":"Anthropic","optional":false},{"name":"AutoGen","optional":false},{"name":"AWS","optional":false},{"name":"AWS Bedrock","optional":false},{"name":"Azure","optional":false},{"name":"Azure AKS","optional":false},{"name":"Azure DevOps","optional":false},{"name":"CI/CD","optional":false},{"name":"CrewAI","optional":false},{"name":"Databricks","optional":false},{"name":"Docker","optional":false},{"name":"Embeddings","optional":false},{"name":"Feature Store","optional":false},{"name":"GCP","optional":false},{"name":"GitHub Actions","optional":false},{"name":"Google ADK","optional":false},{"name":"Google AI Studio","optional":false},{"name":"Google Cloud Run","optional":false},{"name":"Hugging Face","optional":false},{"name":"Kubeflow","optional":false},{"name":"Kubernetes","optional":false},{"name":"LangChain","optional":false},{"name":"LangGraph","optional":false},{"name":"LlamaIndex","optional":false},{"name":"LLM","optional":false},{"name":"LLM Evaluation","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"LLMOps","optional":false},{"name":"Machine Learning","optional":false},{"name":"MLFlow","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"OpenAI","optional":false},{"name":"RAG","optional":false},{"name":"Vertex AI","optional":false},{"name":"A/B Testing","optional":true}],"status":"live","first_seen_at":"2026-01-30T16:52:04Z","employer_posted_date":"2026-10-05","last_verified_at":"2026-10-06T02:05:51Z","board_verified":true,"closed_at":null,"days_open":248,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":247},"description":"About the Role\nLead AI Engineer\nWe’re seeking a Lead AI Engineer who can design, build, and operationalise advanced AI, Machine Learning, and Generative AI systems at enterprise scale. The focus of this role is to bridge the gap between AI prototypes and embedding data and AI solutions in business. You’ll scale AI solutions responsibly and reliably, ensuring they move from lab to live by building the right solutions, practices, and guardrails while ensuring business value creation and impact.\nIn this position you will play a key part in:\nDesigning and delivering end-to-end AI/ML systems, from data preparation and model development to model deployment, feature stores, model management and monitoring model management \nDelivering solutions using the latest GenAI and Agentic Frameworks, such as ADK, Langgraph, Microsoft Agent Framework, Llamaindex and other \nTranslating AI use case requirements into data and AI architectures using the most suitable cloud services across hyperscalars \nLeading multi-disciplinary teams to execute complex requirements\nArchitecting and implementing Generative AI solutions, including RAG pipelines, agentic workflows, and orchestration of large language models across Azure, GCP, or AWS. \nEmbedding safety, evaluation, and assurance mechanisms across the AI lifecycle, ensuring solutions are ethical, explainable, and responsible. \nCollaborating with Product Managers, Data Scientists and Business stakeholders to ensure AI solutions drives business value and impact.\nAs part of your role, you will also have the opportunity to contribute to the business and your own personal growth, through activities that form part of the following categories:\nBusiness Development - Build client-ready demos/POVs, support proposals and technical deep-dives, and showcase delivery patterns. \nInternal contribution - Build reusable assets and frameworks that accelerate delivery across accounts and support capability development by contributing to our internal communities and best practices. \nCapability Development - Contribute to thought leadership, blog posts, or internal accelerator development in emerging AI engineering topics such as Agentic AI, LLMOps, or evaluation frameworks. \nWhat you will bring\nWe’d love to meet someone with:\nExperience working in a major Consulting firm, and/or in industry but having a Consulting mindset with a proven ability to be successful in a matrixed organisation, and to enlist support and commitment from peers in selling and delivering solutions. Experience of working with client sponsors, both technical and non-technical, to collaboratively design requirements and build out solutions. \nExperience of designing and implementing MLOPs strategy and framework and proven track record in designing and delivering AI/ML solutions at scale, from concept to production. \nDeep understanding of Generative AI and Agentic AI - RAG pipelines, embeddings, evaluation harnesses, and orchestration frameworks. \nExperience designing cloud-native data and AI architectures across Azure, GCP, AWS and/or Databricks. \nThe ability to demonstrate the potential that scaling AI unlocks business value and impact. \nExperience Required\nYour Technical Expertise:\nThis list shows the technologies we work with most often. We don’t expect you to have experience in all of them - what matters is a strong foundation and a good cross-section of these skills, along with the adaptability and curiosity to learn new tools as projects demand. We like to innovate and need self-driven, fast-paced learners in our team.\n Experience with deploying and scaling AI solutions using at least one major cloud platform: Azure (Foundry, AI Studio, OpenAI, AKS), GCP (Vertex AI, Cloud Run), AWS (Bedrock, SageMaker) \nExperience building and automating AI/ML pipelines using tools such as MLflow, Kubeflow, Azure ML, Vertex Pipelines, Airflow or Google ADK \nHands-on experience with Generative and Agentic AI frameworks such as LangChain, LlamaIndex, CrewAI, Autogen, Google ADK, or similar. \nAbility to design and implement RAG pipelines, agentic workflows, MCP and integration with LLM APIs (OpenAI, Anthropic, Hugging Face OR similar). \nProficiency in CI/CD and containerisation: GitHub Actions, Azure DevOps, Docker, Kubernetes.Nice to haves:\n\nFamiliarity with evaluating AI system performance, including prompt evaluation, A/B testing, and quality assessment frameworks. \nUnderstanding of modern data patterns: lakehouse architectures, vector databases, and relational/NoSQL stores \nFamiliarity with API gateways, event streaming and general integration patterns.Eligibility:\n\nYou need to have resided in the UK for the last 5 years to be able to apply for this role\nAbout Capgemini\nWHAT YOU'LL LOVE ABOUT WORKING HERE\nWe’re a fantastic team of bright, ambitious people who love bringing the latest tech to real clients in production to make a meaningful difference. We work across both the public and private sectors, and our impact is tangible because we innovate, we deploy, and you will see your work come to life in the real world.\nTechnology moves fast, and so do we. We’re a group of true tech enthusiasts who push boundaries, experiment freely, and are trusted at Capgemini to explore what comes next. Our in-house projects highlight what’s possible with the newest models and agentic frameworks.\nWe’re looking for more people with the curiosity, drive, and self-starting spirit of real innovators, people who love technology and want to build the future with us.\nNEED TO KNOW\nWe are delighted to have received the “Glassdoor Best Places to work UK’ accolade for 2 consecutive years, to see what it’s like to work at Capgemini, visit our Glassdoor page\nAt Capgemini we don’t just believe in Diversity & Inclusion, we actively go out to making it a working reality. Driven by our core values and Active Inclusion Campaign, we build environments where you can bring you whole self to work.\nWe aim to build an environment where employees can enjoy a positive work-life balance. We embed hybrid working in all that we do and make flexible working arrangements the day-to-day reality for our people. All UK employees are eligible to request flexible working arrangements.\nEmployee wellbeing is vitally important to us as an organisation. We see a healthy and happy workforce a critical component for us to achieve our organisational ambitions. To help support wellbeing we have trained ‘Mental Health Champions’ across each of our business areas. We have also invested in wellbeing apps such as Thrive and Peppy.\nWe’re also focused on using tech to have a positive social impact. So, we’re working to reduce our own carbon footprint and improve everyone’s access to a digital world. It’s something we’re really serious about. In fact, we were even named as one of the world’s most ethical companies by the Ethisphere Institute for the 10th year. 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