{"id":1506800,"url":"https://alion.io/job/live-connections-ai-engineer","title":"AI Engineer","company":{"id":3800101,"name":"Live Connections","domain":"livecjobs.com","url":"https://alion.io/company/live-connections","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":["Hyderabad, India","Bengaluru, India","Pune, 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Agents","optional":true},{"name":"Anthropic","optional":true},{"name":"CI/CD","optional":true},{"name":"Docker","optional":true},{"name":"FAISS","optional":true},{"name":"Gemini","optional":true},{"name":"Kubernetes","optional":true},{"name":"LangChain","optional":true},{"name":"LlamaIndex","optional":true},{"name":"Milvus","optional":true},{"name":"OpenAI","optional":true},{"name":"Pinecone","optional":true},{"name":"Weaviate","optional":true}],"status":"live","first_seen_at":"2026-09-30T05:12:37Z","employer_posted_date":null,"last_verified_at":"2026-09-30T05:12:37Z","board_verified":false,"closed_at":null,"days_open":6,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":6},"description":"AI Engineer\n\nRole Overview : \n\nWe are looking for an experienced AI Engineer with strong hands-on expertise in Python, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and cloud platforms such as AWS, Azure or GCP.\n\nThe ideal candidate will be responsible for designing, developing and deploying AI-powered solutions, with a strong focus on Generative AI, LLM applications and scalable cloud-based AI systems.\n\nKey Responsibilities : \n\n- Design, develop and deploy AI/ML and Generative AI solutions for enterprise use cases.\n\n- Build and implement LLM-powered applications using modern Generative AI frameworks and techniques.\n\n- Develop RAG pipelines for enterprise knowledge retrieval and question-answering applications.\n\n- Work with embeddings, vector databases, semantic search and document retrieval systems.\n\n- Develop scalable AI applications and services using Python.\n\n- Integrate LLMs with existing applications, APIs, data platforms and enterprise systems.\n\n- Design and implement prompt engineering, context management and evaluation strategies.\n\n- Deploy AI/ML solutions on AWS, Azure or GCP.\n\n- Build production-ready AI services with appropriate monitoring, logging and performance optimisation.\n\n- Collaborate with Data Scientists, ML Engineers, Data Engineers and product teams to translate business requirements into AI solutions.\n\n- Evaluate LLM performance, response quality, latency and cost, and continuously optimise AI solutions.\n\n- Stay updated with emerging developments in Generative AI, LLMs, RAG and AI engineering.\n\nRequired Skills : \n\n- Strong hands-on experience with Python.\n\n- Experience building Generative AI / AI applications.\n\n- Strong understanding of LLMs and their practical implementation.\n\n- Hands-on experience developing RAG-based applications.\n\n- Knowledge of embeddings, vector databases and semantic search.\n\n- Experience with at least one major cloud platform : AWS, Microsoft Azure, or Google Cloud Platform (GCP).\n\n- Strong understanding of APIs, microservices and cloud-based application development.\n\n- Experience with AI/ML model integration and deployment.\n\n- Good understanding of software engineering principles, version control and development best practices.\n\nGood to Have : \n\n- Experience with frameworks such as LangChain, LlamaIndex or similar.\n\n- Exposure to OpenAI, Azure OpenAI, Anthropic, Gemini or other LLM platforms.\n\n- Experience with vector databases such as Pinecone, FAISS, Weaviate, Milvus or similar.\n\n- Knowledge of Docker and Kubernetes.\n\n- Experience with CI/CD and cloud-native deployments.\n\n- Exposure to Agentic AI and AI agents.\n\n- Experience with LLM evaluation, observability and responsible AI practices.\n\nKey Competencies : \n\n- Strong analytical and problem-solving skills.\n\n- Ability to design scalable and production-ready AI solutions.\n\n- Strong understanding of emerging Generative AI technologies.\n\n- Ability to work collaboratively with cross-functional teams.\n\n- Strong communication and technical documentation skills\nSkills\nPython, Generative AI, LLM, RAG, AWS, LangChain, Artificial Intelligence, Prompt Engineering, Agentic 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