{"id":2802956,"url":"https://alion.io/job/deqode-generative-ai-agentic-ai-engineer","title":"Generative AI & Agentic AI Engineer","company":{"id":3798374,"name":"Deqode","domain":"deqode.com","url":"https://alion.io/company/deqode","size_band":"1-10","is_staffing_agency":false,"employer_type":"services","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":19500,"max_usd":43000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":29},"experience_years_min":5,"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":"Chroma","optional":false},{"name":"CI/CD","optional":false},{"name":"Claude","optional":false},{"name":"CrewAI","optional":false},{"name":"Django","optional":false},{"name":"Docker","optional":false},{"name":"Embeddings","optional":false},{"name":"FAISS","optional":false},{"name":"FastAPI","optional":false},{"name":"Flask","optional":false},{"name":"GCP","optional":false},{"name":"Gemini","optional":false},{"name":"Git","optional":false},{"name":"Hallucination","optional":false},{"name":"Hugging Face","optional":false},{"name":"LangChain","optional":false},{"name":"LangGraph","optional":false},{"name":"Llama","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"NumPy","optional":false},{"name":"OpenAI","optional":false},{"name":"Pandas","optional":false},{"name":"Pinecone","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"RAG","optional":false},{"name":"Rest API","optional":false},{"name":"Scikit-learn","optional":false},{"name":"Semantic Search","optional":false},{"name":"Semantic Search","optional":false},{"name":"Weaviate","optional":false}],"status":"live","first_seen_at":"2026-07-27T07:17:19Z","employer_posted_date":null,"last_verified_at":"2026-07-27T07:17:19Z","board_verified":false,"closed_at":null,"days_open":84,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":84},"description":"Role Summary:\n\nWe are seeking a skilled GenAI & Agentic AI Engineer with strong experience in building end-to-end AI/ML solutions, Generative AI applications, and agent-based automation workflows. The ideal candidate will have a solid background in machine learning along with hands-on expertise in LLMs, RAG, embeddings, vector databases, and Agentic AI frameworks such as CrewAI, AutoGen, LangGraph, or LangChain Agents.\n\nKey Responsibilities:\n\n- Build and deploy GenAI applications using LLMs (OpenAI, Azure OpenAI, Claude, Gemini, Llama, etc.).\n\n- Develop Agentic AI workflows using frameworks such as CrewAI, AutoGen, LangGraph, or LangChain Agents.\n\n- Design and implement RAG pipelines, vector search solutions, and embedding-based retrieval systems.\n\n- Build scalable AI services using Python, FastAPI/Flask, and cloud platforms (Azure/AWS/GCP).\n\n- Collaborate with cross-functional teams to define use cases and convert them into production-ready GenAI solutions.\n\n- Implement hallucination reduction, prompt-engineering strategies, and model evaluation methods.\n\n- Integrate LLMs with enterprise applications, APIs, and automation workflows.\n\n- Work with vector databases (FAISS, Pinecone, Chroma, Weaviate) for semantic search.\n\n- Monitor, evaluate, and optimize GenAI models for accuracy, performance, and cost.\n\nRequired Skills & Experience:\n\n- 5+ years of experience in AI/ML, including model development, data preprocessing, EDA, training, and evaluation.\n\n- 2+ years of hands-on experience in Generative AI (LLMs, embeddings, RAG, LLM-based apps).\n\n- 6+ months of hands-on experience with Agentic AI frameworks (CrewAI / AutoGen / LangGraph / LangChain Agents).\n\n- Strong proficiency in Python and ML libraries (Scikit-learn, Pandas, NumPy).\n\n- Experience with OpenAI APIs, Azure OpenAI, HuggingFace, and prompt engineering.\n\n- Familiarity with building scalable APIs using FastAPI, Flask, or Django.\n\n- Hands-on knowledge of cloud services (Azure/AWS/GCP) for AI deployment.\n\n- Strong understanding of REST APIs, microservices, and integration patterns.\n\n- Experience with Git, CI/CD, Docker, and model deployment best 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