{"id":1808338,"url":"https://alion.io/job/capgemini-full-stack-engineer-ai-product","title":"Full stack engineer - AI product","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":"A","score":87,"open_postings":66,"ghost_share":0,"stale_share":0.318,"repost_share":0,"time_to_fill_p50_days":63,"computed_at":"2026-10-03T05:45:00Z"}},"role":"Backend","role_family":"Backend","seniority":null,"employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Warsaw, Poland"],"countries":["PL"],"hiring_countries":["PL"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":51000,"max_usd":96000,"period":"year","method":"role_country_seniority_unknown","sample_n":693},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"A2A","optional":false},{"name":"AI Agents","optional":false},{"name":"BigQuery","optional":false},{"name":"CI/CD","optional":false},{"name":"Cypress","optional":false},{"name":"Docker","optional":false},{"name":"Embeddings","optional":false},{"name":"Express","optional":false},{"name":"FastAPI","optional":false},{"name":"Firestore","optional":false},{"name":"Flask","optional":false},{"name":"Function Calling","optional":false},{"name":"GCP","optional":false},{"name":"Git","optional":false},{"name":"Google BigQuery","optional":false},{"name":"JavaScript","optional":false},{"name":"Jest","optional":false},{"name":"LangChain","optional":false},{"name":"LangGraph","optional":false},{"name":"LLM","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"Nest.JS","optional":false},{"name":"Node JS","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"React.js","optional":false},{"name":"Rest API","optional":false},{"name":"Tailwind CSS","optional":false},{"name":"Tool Use","optional":false},{"name":"TypeScript","optional":false},{"name":"Vertex AI","optional":false}],"status":"live","first_seen_at":"2026-09-08T08:36:25Z","employer_posted_date":"2026-09-08","last_verified_at":"2026-10-04T02:51:38Z","board_verified":true,"closed_at":null,"days_open":25,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":25},"description":"Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you’d like, where you’ll be supported and inspired by a collaborative community of colleagues around the world, and where you’ll be able to reimagine what’s possible. Join us and help the world’s leading organizations unlock the value of technology and build a more sustainable, more inclusive world.\nYour role\nAs a Full Stack Engineer for Neo within Capgemini, you will help build the next generation of Neo, the Group-wide AI platform connecting employees with tools, enterprise knowledge, data and intelligent workflows. This is a hands-on engineering role for someone who can work across frontend, backend and AI-enabled product flows, while contributing to fast iteration, technical quality and scalable implementation.\nYou will build user-facing AI experiences, backend services and middleware components that connect Neo's frontend with AI/LLM backends, routing services, data sources and enterprise integrations. The role requires strong skills in React, JavaScript/TypeScript, Python, API development, cloud-native engineering and AI-ready application patterns.\nIn this role you will play a key role in:\nBuild highly interactive and scalable frontend experiences using React or comparable frameworks, with strong focus on performance, usability and maintainability.\nDevelop backend services and APIs using JavaScript/TypeScript, Node.js and frameworks such as Express.js or NestJS.\nDevelop Python-based AI/LLM components, automation scripts, data-processing logic and integration services where required.\nBuild middleware capabilities that connect the frontend with AI backends, including session management, prompt handling, permissions logic, routing flags and data workflows.\nSupport AI product flows such as conversational interfaces, prompt libraries, file upload flows, RAG-based answers, structured responses, citations and feedback mechanisms.\nIntegrate with enterprise services, third-party SaaS platforms, connectors, agents and task automation flows.\nWork with cloud services, preferably GCP, to support scalable, observable and production-ready deployments.\nWrite clean, testable and maintainable code with proper unit, integration and end-to-end test coverage.\nCollaborate closely with Product, UX/UI, Engineering Leads, Data Science, Backend, Routing Layer and QA teams to deliver high-quality features.\nPrototype, test and iterate quickly in ambiguous areas where AI behavior, user needs and technical feasibility need to be shaped together.\nYour profile\nBachelor's or Master's degree in Computer Science, Engineering or a related field, or equivalent practical experience.\nStrong hands-on full-stack development experience across frontend, backend and API-driven products.\nStrong frontend experience with React, including component-based development, state management, rendering performance and API integration.\nExperience with modern frontend tooling such as Tailwind CSS, Jest, Cypress, Nx, Module Federation or comparable technologies.\nStrong backend experience with JavaScript/TypeScript, Node.js and frameworks such as Express.js or NestJS.\nStrong Python skills, ideally applied in AI/LLM/ML contexts such as data processing, orchestration, model integration, RAG pipelines, evaluation scripts or backend AI services.\nSolid understanding of REST APIs, microservices, middleware, authentication, authorization, RBAC and secure enterprise integration.\nUnderstanding of AI application patterns, including LLMs, prompt engineering, RAG, embeddings, vector search, tool calling and conversational interfaces.\nExperience with GCP or other cloud platforms, CI/CD, Git workflows, Docker and production deployment practices.\nAbility to debug complex issues across UI, backend services, cloud infrastructure, data flows and AI model behavior.\nProduct mindset with the ability to build fast, test assumptions and iterate based on user feedback.\nBonus:\nExperience with LangChain, LangGraph, FastAPI, Flask, Vertex AI, BigQuery, Firestore or Apigee.\nExperience with MCP, AI agents, Agent2Agent patterns or enterprise conversational interfaces.\nKnowledge of OAuth2, SAML, OpenID Connect or enterprise SSO flows.\nFoundational UX and product design understanding.\nZero-to-one product experience in fast-moving environments.\nWhat you'll love about working here\nAt the heart of our mission is your career growth. Our array of career growth programs and diverse professions are crafted to support you in exploring a world of opportunities.\nWe recognize the significance of flexible work arrangements to provide support. Be it remote work, or flexible work hours, you will get an environment to maintain a healthy work life balance.\nThe opportunity to build an AI-first enterprise platform from the inside.\nThe chance to work across React, Python, backend services, cloud, agents and AI product experiences.\nA role where engineering, product thinking and AI innovation are deeply connected.\nApplication:\nAs part of our recruitment process, identity verification will be conducted through inspection of your ID card, and background checks may be carried out as required.\nCapgemini is an AI-powered global business and technology transformation partner, delivering tangible business value. We imagine the future of organizations and make it real with AI, technology and people. With our strong heritage of nearly 60 years, we are a responsible and diverse group of 420,000 team members in more than 50 countries. We deliver end-to-end services and solutions with our deep industry expertise and strong partner ecosystem, leveraging our capabilities across strategy, technology, design, engineering and business operations. The Group reported 2024 global revenues of €22.1 billion.\nMake it real | www.capgemini.com","description_format":"text","description_chars":5825,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":true},"security_clearance":false,"languages":[]},"benefits":["Flexible schedule"],"hiring_locations":[{"name":"Poland","iso":"PL","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Artificial Intelligence","Cybersecurity","Government","Research Institutes"],"lifecycle":[{"event":"open","at":"2026-10-03T19:36:31Z"}],"visa":[],"liveness":{"score":67,"band":"ok","label":"Likely open","p_open":1,"p_active":0.739,"p_room":0.9,"age_days":25,"expected_fill_days":63,"reasons":["conf:0","win:mid","comp:brand"],"computed_at":"2026-10-04T03:05:01Z"},"pay":null,"html_url":"https://alion.io/job/capgemini-full-stack-engineer-ai-product","json_url":"https://alion.io/job/capgemini-full-stack-engineer-ai-product.json","meta":{"generated_at":"2026-10-04T03:05:01Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":4674,"day_limit":5000,"remaining_today":326,"minute_limit":60,"resets_at":"2026-10-05T00:00:00Z"}}}