{"id":1746924,"url":"https://alion.io/job/infosys-gen-ai-consultant","title":"Gen AI Consultant","company":{"id":223,"name":"Infosys","domain":"infosys.com","url":"https://alion.io/company/infosys","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":95,"open_postings":233,"ghost_share":0,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":93,"computed_at":"2026-10-24T06:02:35Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"junior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":12000,"max_usd":32000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":16},"experience_years_min":2,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"AutoGen","optional":false},{"name":"AWS","optional":false},{"name":"Azure","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":"Fine-tuning","optional":false},{"name":"GCP","optional":false},{"name":"Git","optional":false},{"name":"Hugging Face","optional":false},{"name":"Kubernetes","optional":false},{"name":"LangChain","optional":false},{"name":"LangGraph","optional":false},{"name":"Llama","optional":false},{"name":"Machine Learning","optional":false},{"name":"Milvus","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"Multi-Agent Systems","optional":false},{"name":"NLP","optional":false},{"name":"OpenAI","optional":false},{"name":"Pinecone","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Rest API","optional":false},{"name":"Semantic Kernel","optional":false},{"name":"Weaviate","optional":false}],"status":"live","first_seen_at":"2026-10-01T08:23:49Z","employer_posted_date":"2026-10-03","last_verified_at":"2026-10-24T15:52:09Z","board_verified":true,"closed_at":null,"days_open":23,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":23},"description":"We are seeking a highly skilled Generative AI Engineer with 2 to 5 years of experience in designing, developing, and deploying AI-powered applications. The ideal candidate should have hands-on expertise in LLMs, RAG, Agentic AI, Prompt Engineering, Python, LangChain, Vector Databases, and AI Model Integration.\nResponsibilities\nDesign and develop Generative AI solutions using Large Language Models (LLMs).\nBuild and optimize RAG (Retrieval-Augmented Generation) pipelines.\nDevelop AI Agents using frameworks such as LangChain, LangGraph, AutoGen, CrewAI, or similar.\nIntegrate OpenAI, Azure OpenAI, Claude, Gemini, Llama, or other foundation models into enterprise applications.\nImplement prompt engineering and fine-tuning strategies to improve AI outputs.\nBuild APIs and microservices to serve AI applications.\nWork with vector databases such as Pinecone, ChromaDB, FAISS, Weaviate, or Milvus.\nCollaborate with business and technical teams to translate requirements into AI solutions.\nOptimize model performance, scalability, security, and cost.\nConduct testing, validation, and deployment of AI systems.\nTechnical requirements\nHands-on experience with Generative AI, LLMs, and Prompt Engineering.\nExperience with LangChain, LangGraph, CrewAI, AutoGen, Semantic Kernel, or similar frameworks.\nKnowledge of RAG Architecture and Vector Databases.\nExperience with Azure OpenAI, OpenAI APIs, Gemini, Claude, Llama, or Hugging Face Models.\nUnderstanding of NLP, Machine Learning, and Deep Learning concepts.\nExperience with REST APIs and microservices.\nKnowledge of Git, Docker, and CI/CD pipelines.\nFamiliarity with cloud platforms such as Azure, AWS, or GCP.\nAdditional responsibilities\nKnowledge of MCP (Model Context Protocol).\nExperience in multi-agent systems and Agentic AI workflows.\nExposure to fine-tuning, embeddings, and model evaluation.\nExperience with Kubernetes and MLOps practices.\nKnowledge of AI governance, security, and responsible AI practices.\nPreferred skills\nTechnology->AI-Generative AI->Generative AI for Data Analytics\nEducation\nMCA,MTech,Bachelor of 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