{"id":1905893,"url":"https://alion.io/job/capgemini-genai-agentic-ai-developer-2","title":"GenAI / Agentic AI Developer","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":81,"open_postings":1720,"ghost_share":0,"stale_share":0.757,"repost_share":0.001,"time_to_fill_p50_days":27,"computed_at":"2026-10-10T05:45:15Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"explicit","locations":["New York, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":122000,"max_usd":232000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":987},"experience_years_min":5,"visa_sponsorship":true,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Anthropic","optional":false},{"name":"AutoGen","optional":false},{"name":"AWS","optional":false},{"name":"AWS Bedrock","optional":false},{"name":"Azure","optional":false},{"name":"Chroma","optional":false},{"name":"CI/CD","optional":false},{"name":"Claude","optional":false},{"name":"CrewAI","optional":false},{"name":"Docker","optional":false},{"name":"Embeddings","optional":false},{"name":"FAISS","optional":false},{"name":"FastAPI","optional":false},{"name":"Flask","optional":false},{"name":"Function Calling","optional":false},{"name":"Human-in-the-Loop","optional":false},{"name":"Kubernetes","optional":false},{"name":"LangChain","optional":false},{"name":"LangGraph","optional":false},{"name":"Llama","optional":false},{"name":"LlamaIndex","optional":false},{"name":"LLMOps","optional":false},{"name":"Milvus","optional":false},{"name":"Multi-Agent Systems","optional":false},{"name":"OpenAI","optional":false},{"name":"OpenSearch","optional":false},{"name":"pgvector","optional":false},{"name":"Pinecone","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Reranking","optional":false},{"name":"Rest API","optional":false},{"name":"Semantic Kernel","optional":false},{"name":"Semantic Search","optional":false},{"name":"Semantic Search","optional":false},{"name":"Tool Use","optional":false},{"name":"Weaviate","optional":false},{"name":"Amazon SageMaker","optional":true},{"name":"Arize Phoenix","optional":true},{"name":"GCP","optional":true},{"name":"GraphRAG","optional":true},{"name":"Knowledge Graph","optional":true},{"name":"LangSmith","optional":true},{"name":"LLM Guardrails","optional":true},{"name":"MLFlow","optional":true},{"name":"Model Context Protocol","optional":true},{"name":"Neo4j","optional":true},{"name":"OpenTelemetry","optional":true},{"name":"PostgreSQL","optional":true},{"name":"Ragas","optional":true},{"name":"TruLens","optional":true},{"name":"Vertex AI","optional":true}],"status":"live","first_seen_at":"2026-07-08T04:32:16Z","employer_posted_date":"2026-08-12","last_verified_at":"2026-10-11T01:27:19Z","board_verified":true,"closed_at":null,"days_open":94,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":94},"description":"Work Authorization\nCandidates must be authorized to work in the United States without current or future employer sponsorship.\nVisa sponsorship is not available for this position. Candidates requiring sponsorship now or in the future, including H-1B, OPT, CPT, F-1, TN, E-3, L-1, or similar employment-based sponsorship, are not eligible for consideration.\nJob Description\nWe are seeking a highly skilled and hands-on GenAI / Agentic AI Developer to design, build, and deploy enterprise-grade AI solutions powered by Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and multi-agent architectures.\nThe ideal candidate will have strong Python development expertise and practical experience implementing GenAI applications, agent orchestration frameworks, vector search technologies, and cloud-native AI solutions. This role requires someone who can move from proof-of-concept to production while ensuring scalability, reliability, security, and business value.\nKey Responsibilities\nDesign and develop GenAI solutions using LLMs, RAG, tool calling, and agent-based architectures.\nBuild and orchestrate multi-agent workflows, including planner, retriever, executor, validator, and human-in-the-loop patterns.\nDevelop backend services and APIs using Python, FastAPI, Flask, REST APIs, and microservices.\nDesign and implement document ingestion, embedding generation, vector indexing, reranking, and retrieval pipelines.\nIntegrate AI applications with enterprise systems, APIs, databases, document repositories, and cloud services.\nDeploy, monitor, and support GenAI applications using Docker, Kubernetes, CI/CD pipelines, and cloud platforms.\nImplement LLMOps best practices, including model evaluation, prompt management, monitoring, logging, observability, and cost optimization.\nCollaborate with business and technology stakeholders to deliver scalable AI solutions that generate measurable business outcomes.\nRequired Qualifications\nBachelor's degree in Computer Science, Engineering, Data Science, or a related field, or equivalent professional experience.\n5+ years of hands-on Python development experience.\nExperience building and deploying GenAI or Agentic AI applications in enterprise environments.\nHands-on experience with one or more of the following:\nLangGraph\nLangChain\nAutoGen\nCrewAI\nSemantic Kernel\nLlamaIndex\nStrong understanding of:\nRetrieval-Augmented Generation (RAG)\nEmbeddings\nPrompt Engineering\nSemantic Search\nVector Databases\nExperience working with one or more of the following:\nOpenAI\nAzure OpenAI\nAWS Bedrock\nAnthropic Claude\nGemini\nLlama\nMistral\nExperience with vector platforms such as:\nOpenSearch\nPinecone\nChroma\nFAISS\nWeaviate\nMilvus\nAzure AI Search\npgvector\nExperience developing REST APIs and cloud-native applications.\nKnowledge of Docker, Kubernetes, CI/CD, and software engineering best practices.\nExperience working with structured and unstructured data sources, including documents, PDFs, APIs, databases, and knowledge repositories.\nPreferred Qualifications\nExperience designing and deploying multi-agent AI systems.\nExperience with tool calling, memory management, autonomous planning, reflection, and evaluation techniques.\nExposure to:\nMCP (Model Context Protocol)\nGraphRAG\nNeo4j\nKnowledge Graphs\nEntity Extraction\nExperience with LLMOps tools such as:\nLangSmith\nMLflow\nPhoenix\nRagas\nTruLens\nArize\nOpenTelemetry\nExperience with:\nAzure AI Foundry\nAzure OpenAI\nAzure AI Search\nAWS Bedrock\nAWS SageMaker\nGCP Vertex AI\nKnowledge of AI governance, responsible AI, AI guardrails, prompt injection prevention, PII masking, and access controls.\nRequired Candidate Experience\nCandidates must be able to clearly explain at least one end-to-end GenAI or Agentic AI implementation, including:\nBusiness problem being solved\nOverall solution architecture\nLLMs and frameworks leveraged\nAgent orchestration approach\nRAG and vector search design\nDeployment strategy\nEvaluation and monitoring methodology\nBusiness impact and measurable outcomes\nFor this role, the gross annual starting base salary is 100,000-150,000 (full-time). This covers base pay only; any bonuses, incentives, and benefits will be discussed later in the recruitment process. Candidates with additional experience or qualifications may receive a higher offer, determined by objective, gender-neutral criteria and consistent with our pay principles. If a collective labour agreement applies, we will explain the relevant pay terms at the interview stage. Note: We never ask for your current or previous salary during our hiring process.","description_format":"text","description_chars":4544,"description_truncated":false,"requirements":{"experience_years_min":5,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":true},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Cybersecurity","Government","Science & Engineering","Research Institutes"],"lifecycle":[{"event":"open","at":"2026-10-05T12:51:38Z"},{"event":"close","at":"2026-10-05T21:09:41Z"},{"event":"reopen","at":"2026-10-06T07:01:33Z"}],"visa":[{"country":"US","licensed_sponsor":true,"evidence":"H-1B filings in 12 months: 2,076 · green card filings: 82","filings_12m":2076,"filings_prev_12m":2803,"green_card_filings_12m":82,"median_offered_wage_usd":132120,"route":null,"cap_exempt":false,"checked_at":"2026-10-03T21:08:04+00:00","sources":["US Department of Labor: LCA disclosure data (H-1B, H-1B1, E-3)","US Department of Labor: PERM disclosure data (green cards)"],"filings_for_role_12m":1012}],"liveness":{"score":10,"band":"cold","label":"Long shot","p_open":1,"p_active":0.354,"p_room":0.28,"age_days":94,"expected_fill_days":27,"reasons":["conf:1","stale_co","velocity","win:tail","crowd:brand"],"computed_at":"2026-10-10T05:45:15Z"},"pay":null,"html_url":"https://alion.io/job/capgemini-genai-agentic-ai-developer-2","json_url":"https://alion.io/job/capgemini-genai-agentic-ai-developer-2.json","meta":{"generated_at":"2026-10-11T03:02:53Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":315,"day_limit":5000,"remaining_today":4685,"minute_limit":60,"resets_at":"2026-10-12T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":145},"rest":"https://alion.io/mcp/rest/get_company?id=145"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fcapgemini-genai-agentic-ai-developer-2"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fcapgemini-genai-agentic-ai-developer-2"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fcapgemini-genai-agentic-ai-developer-2"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/capgemini-genai-agentic-ai-developer-2\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fcapgemini-genai-agentic-ai-developer-2"}]}