{"id":1272783,"url":"https://alion.io/job/acronotics-generative-ai-engineer","title":"Generative AI Engineer","company":{"id":3808966,"name":"Acronotics","domain":"acronotics.com","url":"https://alion.io/company/acronotics","size_band":null,"is_staffing_agency":false,"employer_type":"direct","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":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":["India"],"countries":["IN"],"hiring_countries":["IN"],"hiring_countries_total":1,"salary":{"min":2000000,"max":3000000,"currency":"INR","period":"year","gross":true,"usd_annual":31446},"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"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":"CI/CD","optional":false},{"name":"Claude","optional":false},{"name":"CrewAI","optional":false},{"name":"Databricks","optional":false},{"name":"DeepEval","optional":false},{"name":"Docker","optional":false},{"name":"Embeddings","optional":false},{"name":"FAISS","optional":false},{"name":"Fine-tuning","optional":false},{"name":"GCP","optional":false},{"name":"Gemini","optional":false},{"name":"GitHub Actions","optional":false},{"name":"Hugging Face","optional":false},{"name":"Hybrid Search","optional":false},{"name":"Kubernetes","optional":false},{"name":"LangChain","optional":false},{"name":"LangGraph","optional":false},{"name":"LangSmith","optional":false},{"name":"LLM","optional":false},{"name":"LoRA","optional":false},{"name":"Milvus","optional":false},{"name":"MLFlow","optional":false},{"name":"Neo4j","optional":false},{"name":"OpenAI","optional":false},{"name":"OpenTelemetry","optional":false},{"name":"PEFT","optional":false},{"name":"pgvector","optional":false},{"name":"Phidata","optional":false},{"name":"Pinecone","optional":false},{"name":"Python","optional":false},{"name":"Qdrant","optional":false},{"name":"QLoRA","optional":false},{"name":"RAG","optional":false},{"name":"Rest API","optional":false},{"name":"SQL","optional":false},{"name":"Tool Use","optional":false},{"name":"Vertex AI","optional":false},{"name":"Computer Vision","optional":true},{"name":"FastAPI","optional":true},{"name":"JavaScript","optional":true},{"name":"Node JS","optional":true},{"name":"OCR","optional":true},{"name":"OpenCV","optional":true},{"name":"PostgreSQL","optional":true},{"name":"Transformers","optional":true},{"name":"YOLO","optional":true}],"status":"live","first_seen_at":"2026-08-31T11:29:59Z","employer_posted_date":null,"last_verified_at":"2026-08-31T11:29:59Z","board_verified":false,"closed_at":null,"days_open":29,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":29},"description":"Job Description : Gen AI Engineer\n\nExperience Required : 5+ Years\n\nWork Mode : Remote\n\nAbout the Role :\n\nWe are looking for an experienced Gen AI Engineer to design, build, and deploy production-grade Generative AI and Agentic AI systems. The ideal candidate has hands-on experience across the full Gen AI stack - from LLM orchestration and RAG pipeline architecture to fine-tuning, deployment, and monitoring - and is comfortable working independently in a remote-first environment.\n\nKey Responsibilities :\n\n- Design, build, and deploy Retrieval-Augmented Generation (RAG) pipelines, including semantic chunking, embedding generation, and hybrid retrieval strategies.\n\n- Architect and implement Agentic AI workflows using frameworks such as LangChain, LangGraph, CrewAI, AutoGen, or Phidata for multi-step, tool-calling agent orchestration.\n\n- Fine-tune and optimize LLMs using parameter-efficient techniques (PEFT, LoRA, QLoRA) for domain-specific use cases.\n\n- Integrate LLM-powered applications (chatbots, copilots, automation agents) with vector databases (Pinecone, Qdrant, Neo4j, pgvector, Milvus, etc.) and graph databases where applicable.\n\n- Build and maintain end-to-end AI pipelines (including on Databricks) for large-scale document ingestion, vectorization, and real-time inference.\n\n- Deploy and manage AI systems on cloud platforms (AWS Bedrock/SageMaker, Azure OpenAI/AI Foundry, GCP Vertex AI) with secure, enterprise-grade configurations.\n\n- Implement MLOps and CI/CD practices - containerization (Docker), orchestration (Kubernetes), experiment tracking (MLflow), and automated deployment pipelines (GitHub Actions).\n\n- Monitor and evaluate production AI systems using tools such as LangSmith, RAGAS, DeepEval, or OpenTelemetry for reliability, drift detection, and performance tracking.\n\n- Collaborate cross-functionally with product, data engineering, and (where applicable) front-end teams to integrate AI capabilities via REST APIs and microservices.\n\n- Stay current with emerging Gen AI research, tools, and best practices, and evaluate their applicability to ongoing projects.\n\nRequired Skills & Experience:\n\n- 5+ years of total IT experience, with significant hands-on experience in Generative AI / Agentic AI (typically 1.5 - 2+ years focused specifically on Gen AI).\n\n- Strong programming proficiency in Python; working knowledge of SQL.\n\n- Practical experience with Agentic AI frameworks: LangChain, LangGraph, CrewAI, AutoGen, Phidata, or similar.\n\n- Experience with LLM providers: OpenAI, Anthropic (Claude), Google Gemini, Hugging Face models.\n\n- Solid understanding of RAG architecture, embeddings, and semantic/hybrid search.\n\n- Experience with vector and/or graph databases (Pinecone, Qdrant, Neo4j, Milvus, ChromaDB, FAISS, pgvector).\n\n- Familiarity with LLM fine-tuning techniques (PEFT, LoRA, QLoRA).\n\n- Working knowledge of cloud platforms (AWS, Azure, or GCP) - particularly their AI/ML services.\n\n- Experience with Databricks for building end-to-end AI pipelines, large-scale data ingestion, and vectorization workflows.\n\n- Experience with Docker, CI/CD pipelines, and basic MLOps practices.\n\n- Strong analytical, problem-solving, and communication skills; ability to work independently in a remote setting.\n\nGood to Have :\n\n- Experience with computer vision (OpenCV, YOLO) or OCR pipelines.\n\n- Familiarity with observability/evaluation tools (LangSmith, RAGAS, DeepEval, MLflow).\n\n- Exposure to REST API/microservices integration (FastAPI, Node.js) for AI-powered web applications.\n\n- Experience with Kubernetes for container orchestration.\n\n- Prior experience in enterprise/regulated environments (secure LLM deployments, private endpoints, Key Vault, etc.).\n\n- Relevant certifications (AWS, Azure AI, DeepLearning.AI, etc.).\nSkills\nMachine Learning, Python, Generative AI, RAG, Databricks","description_format":"text","description_chars":3833,"description_truncated":false,"requirements":{"experience_years_min":5,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[{"name":"India","iso":"IN","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":[],"lifecycle":[{"event":"open","at":"2026-09-26T00:07:01Z"}],"liveness":{"score":39,"band":"fade","label":"Fading","p_open":0.85,"p_active":0.616,"p_room":0.75,"age_days":28,"expected_fill_days":30,"reasons":["seen:28","win:late"],"computed_at":"2026-09-29T05:45:00Z"},"pay":{"stated_usd_annual":31446,"is_top_pay":false},"html_url":"https://alion.io/job/acronotics-generative-ai-engineer","json_url":"https://alion.io/job/acronotics-generative-ai-engineer.json","meta":{"generated_at":"2026-09-30T00:32:14Z","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":340,"day_limit":5000,"remaining_today":4660,"minute_limit":60,"resets_at":"2026-10-01T00:00:00Z"}}}