{"id":3856685,"url":"https://alion.io/job/sunovaa-genai-engineer-ragllm","title":"GenAI Engineer - RAG/LLM","company":{"id":3800722,"name":"Sunovaa","domain":"sunovaa.com","url":"https://alion.io/company/sunovaa-tech","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":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Pune, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"CI/CD","optional":false},{"name":"Docker","optional":false},{"name":"Git","optional":false},{"name":"GraphRAG","optional":false},{"name":"LLM","optional":false},{"name":"NLP","optional":false},{"name":"OpenSearch","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Pytest","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Semantic Search","optional":false},{"name":"AWS","optional":true},{"name":"AWS Bedrock","optional":true},{"name":"Azure","optional":true},{"name":"DeepEval","optional":true},{"name":"FastAPI","optional":true},{"name":"Knowledge Graph","optional":true},{"name":"LangSmith","optional":true},{"name":"Machine Learning","optional":true},{"name":"Model Context Protocol","optional":true},{"name":"Neo4j","optional":true},{"name":"OpenAI","optional":true},{"name":"Pydantic","optional":true}],"status":"live","first_seen_at":"2026-11-06T05:28:32Z","employer_posted_date":null,"last_verified_at":"2026-11-06T05:28:32Z","board_verified":false,"closed_at":null,"days_open":1,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":1},"description":"Job Summary:\n\nWe are looking for an experienced AI / GenAI Software Engineer with 5+ years of software engineering experience and strong expertise in Generative AI, NLP, Large Language Models (LLMs), Information Retrieval and RAG architectures.\n\nThe ideal candidate will have a strong production engineering mindset and experience taking AI solutions from experimentation to reliable, scalable enterprise applications.\n\nKey Responsibilities:\n\n- Design, develop and maintain production-grade AI/GenAI applications using Python.\n\n- Develop enterprise solutions using LLMs, NLP, Prompt Engineering and Retrieval Augmented Generation (RAG).\n\n- Design and implement RAG, hybrid retrieval and GraphRAG architectures.\n\n- Work with vector search and information retrieval technologies, including OpenSearch or similar platforms.\n\n- Develop APIs and AI services using modern Python frameworks and practices.\n\n- Build automated AI evaluation pipelines to measure retrieval quality and LLM output quality.\n\n- Write clean, maintainable and typed Python code using modern Python features.\n\n- Develop comprehensive automated tests using pytest, mocking and unit/integration testing.\n\n- Follow software engineering best practices including Git, merge requests, code reviews, CI/CD and code quality checks.\n\n- Containerize and manage applications using Docker.\n\n- Work across the SDLC and CRISP-DM lifecycle, converting AI experiments into deterministic and production-ready software.\n\n- Collaborate with technical and non-technical stakeholders to understand requirements and deliver practical AI solutions.\n\n- Continuously evaluate emerging GenAI technologies and identify opportunities for business/product improvement.\n\nMandatory Skills:\n\n- 5+ years of professional software engineering experience\n\n- Strong hands-on experience with Python\n\n- Strong experience in Generative AI / LLMs\n\n- Experience with NLP / Information Retrieval\n\n- Hands-on experience with RAG\n\n- Experience with Vector Search / Semantic Search\n\n- Experience with Hybrid Retrieval\n\n- Strong understanding of Prompt Engineering\n\n- Experience developing production-grade AI applications\n\n- Experience with pytest / automated testing\n\n- Experience with Git, code reviews and software development lifecycle\n\n- Experience with Docker / containerization\n\nPreferred Skills:\n\n- GraphRAG\n\n- OpenSearch\n\n- Pydantic\n\n- Async Python / async-await\n\n- FastAPI\n\n- Automated LLM/RAG evaluation\n\n- RAGAS / DeepEval / LangSmith or similar evaluation frameworks\n\n- AWS Bedrock\n\n- Azure OpenAI\n\n- Model Context Protocol (MCP)\n\n- Knowledge Graphs / Neo4j\n\nCandidate Profile:\n\nWe are looking for someone who:\n\n- Has a strong hands-on engineering mindset\n\n- Can build AI solutions beyond prototypes and notebooks\n\n- Understands how to take an AI experiment into production\n\n- Has strong analytical and problem-solving abilities\n\n- Can explain complex AI concepts to technical and non-technical stakeholders\n\n- Learns quickly and adapts to the rapidly evolving GenAI ecosystem\n\n- Takes ownership and works proactively\n\n- Focuses on practical, scalable and reliable solutions\n\nImportant:\n\nCandidates with only basic Python, generic Machine Learning, Data Science, Prompt Engineering or simple Chatbot experience may not be suitable.\n\nStrong hands-on experience in RAG + LLM/GenAI + Python + production software engineering is highly preferred.\nSkills\nArtificial Intelligence, Python, Generative AI, RAG, NLP, Prompt Engineering, FastAPI, 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