{"id":2942527,"url":"https://alion.io/job/mynaksh-senior-ai-engineer","title":"Senior AI Engineer","company":{"id":3236,"name":"MyNaksh","domain":"mynaksh.com","url":"https://alion.io/company/mynaksh","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":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":24000,"max_usd":50000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":38},"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agentic Workflows","optional":false},{"name":"AI Agents","optional":false},{"name":"Embeddings","optional":false},{"name":"LLM","optional":false},{"name":"NLP","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Chroma","optional":true},{"name":"Hugging Face","optional":true},{"name":"LangChain","optional":true},{"name":"LangGraph","optional":true},{"name":"Milvus","optional":true},{"name":"Pinecone","optional":true},{"name":"Recommender Systems","optional":true},{"name":"Transformers","optional":true},{"name":"Weaviate","optional":true}],"status":"live","first_seen_at":"2026-10-20T17:35:15Z","employer_posted_date":null,"last_verified_at":"2026-10-20T17:35:15Z","board_verified":false,"closed_at":null,"days_open":4,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":4},"description":"We are looking for a Senior AI Engineer to build production-grade AI systems focused on conversational AI, personalization, memory, recommendations, and long-term user intelligence. You will work on LLMs, RAG, AI agents, and personalization systems that help AI build persistent context and deliver deeply personalized conversations at scale.\n\nThe core responsibilities for the job include the following:\n\nAI and LLM Engineering: \nBuild and deploy production-grade AI/ML systems end-to-end.\nDevelop LLM, RAG, conversational AI, and agentic workflows.\nBuild orchestration pipelines for AI agents and LLM applications.\nOptimize AI systems for quality, latency, reliability, and cost.\n\nPersonalization and User Intelligence: \nBuild memory systems and long-term conversational context.\nDevelop recommendation and personalization models.\nCombine structured domain knowledge with LLM reasoning and retrieval.\nImprove user intelligence through embeddings, retrieval, and conversational history.\n\nProduction AI Systems: \nDeploy AI models and services to production environments.\nBuild scalable APIs and backend services for AI applications.\nDesign evaluation frameworks and monitoring for LLM performance.\nWork with vector search, embeddings, and retrieval pipelines.\n\nCross-Functional Collaboration: \nPartner with Product, Backend, and Data teams to ship AI-powered features.\nOwn AI features from design through production deployment and monitoring.\n\nRequirements: \n3-5 years of experience in ML, applied ML, NLP, or generative AI engineering.\nStrong proficiency in Python.\nHands-on experience with LLMs, RAG, embeddings, vector search, and conversational AI.\nExperience deploying AI/ML systems into production.\nStrong understanding of ML fundamentals, evaluation, and experimentation.\nExperience with APIs, system design, scalability, and cloud platforms.\nAbility to own AI features end-to-end (design, build, evaluate, deploy).\nStrong software engineering fundamentals with an AI-first mindset.\nOwnership of production AI systems.\nPassion for conversational AI and personalization.\nAbility to solve ambiguous product and engineering problems.\nExperience building scalable AI applications for real users.\n\nGood to Have: \nLangChain or LangGraph.\nVector databases (Pinecone, Weaviate, Chroma, Milvus, etc. ).\nHugging Face Transformers and open-source LLMs.\nMLOps and LLM evaluation frameworks.\nRecommendation systems and personalization engines.\nIndic or multilingual NLP experience.\nSkills\nLLM, LLMs, Python, RAG, large language model, large language models, retrieval","description_format":"text","description_chars":2561,"description_truncated":false,"requirements":{"experience_years_min":3,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Consumer Health Apps","Consumer & Utility Software"],"lifecycle":[{"event":"open","at":"2026-10-20T17:35:15Z"}],"visa":[],"liveness":{"score":90,"band":"hot","label":"Hiring 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