{"id":3810732,"url":"https://alion.io/job/neoqubit-llm-engineer","title":"LLM Engineer","company":{"id":1236,"name":"Neoqubit","domain":"neoqubit.ai","url":"https://alion.io/company/neoqubit","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":"middle","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":null,"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Chroma","optional":false},{"name":"Claude","optional":false},{"name":"Embeddings","optional":false},{"name":"FAISS","optional":false},{"name":"FastAPI","optional":false},{"name":"Few-Shot Learning","optional":false},{"name":"Function Calling","optional":false},{"name":"Hallucination","optional":false},{"name":"Hybrid Search","optional":false},{"name":"LangChain","optional":false},{"name":"LangGraph","optional":false},{"name":"Llama","optional":false},{"name":"LlamaIndex","optional":false},{"name":"LLM","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"Mistral","optional":false},{"name":"Pinecone","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"Qdrant","optional":false},{"name":"RAG","optional":false},{"name":"Reranking","optional":false},{"name":"Rest API","optional":false},{"name":"Semantic Search","optional":false},{"name":"Structured Outputs","optional":false},{"name":"Tokenization","optional":false},{"name":"Transformers","optional":false},{"name":"Weaviate","optional":false},{"name":"AWS","optional":true},{"name":"Azure","optional":true},{"name":"Docker","optional":true},{"name":"Fine-tuning","optional":true},{"name":"GCP","optional":true},{"name":"Hugging Face","optional":true},{"name":"Kubernetes","optional":true},{"name":"LoRA","optional":true},{"name":"Model Context Protocol","optional":true},{"name":"PEFT","optional":true},{"name":"QLoRA","optional":true},{"name":"Quantization","optional":true},{"name":"SFT","optional":true}],"status":"live","first_seen_at":"2026-11-05T14:35:00Z","employer_posted_date":null,"last_verified_at":"2026-11-05T14:35:00Z","board_verified":false,"closed_at":null,"days_open":0,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":0},"description":"We are seeking a skilled and experienced LLM Engineer with 3-5 years of relevant experience in generative AI, large language models (LLMs), and AI application development. The ideal candidate will possess strong Python programming skills, a solid understanding of LLM architecture, and hands-on experience designing, developing, and deploying scalable AI-powered applications. We are looking for an engineer with strong technical fundamentals, practical problem-solving abilities, and the capability to translate complex business requirements into reliable, production-ready AI solutions.\n\nResponsibilities: \nDesign, develop, and deploy LLM-powered applications using commercial and open-source language models.\nBuild and optimize end-to-end Retrieval-Augmented Generation (RAG) pipelines.\nDevelop intelligent AI agents and multi-step workflows using modern AI frameworks.\nImplement prompt engineering, structured output generation, function calling, and tool integration.\nDesign scalable backend services and APIs using Python and FastAPI.\nOptimize LLM applications for accuracy, latency, cost, and performance.\nImplement evaluation frameworks to assess response quality, retrieval performance, and hallucination rates.\nIntegrate vector databases, semantic search, and knowledge retrieval systems.\nImplement appropriate guardrails, monitoring, logging, and error-handling mechanisms.\nCollaborate with cross-functional teams to deliver robust and scalable AI solutions.\n\nRequirements: \nStrong analytical and problem-solving capabilities.\nHands-on experience building and deploying production-grade LLM applications.\nThe ability to explain technical architecture, implementation decisions, and engineering trade-offs.\nStrong coding skills and practical software engineering knowledge.\nThe ability to independently troubleshoot complex technical challenges.\nExcellent technical communication and collaboration skills.\n\nProgramming and Backend Development: \nStrong proficiency in Python and software engineering fundamentals.\nExperience with FastAPI, REST APIs, asynchronous programming, and API integrations.\nStrong understanding of data structures, algorithms, object-oriented programming, and clean coding practices.\n\nLarge Language Models and Generative AI: \nStrong understanding of Transformer architecture, attention mechanisms, tokenization, and embeddings.\nHands-on experience with LLMs such as GPT, Claude, Llama, or Mistral.\nExperience with prompt engineering, few-shot learning, structured outputs, and function calling.\nUnderstanding of context windows, inference parameters, and LLM limitations.\n\nRetrieval-Augmented Generation (RAG): \nHands-on experience developing end-to-end RAG applications.\nExperience with document ingestion, preprocessing, chunking, and embedding generation.\nFamiliarity with vector databases such as FAISS, Pinecone, Qdrant, Chroma, or Weaviate.\nUnderstanding of semantic search, hybrid search, metadata filtering, and reranking.\nAbility to evaluate and improve retrieval quality and answer accuracy.\n\nAI Frameworks and Agentic AI: \nExperience with LangChain, LangGraph, LlamaIndex, or equivalent frameworks.\nUnderstanding of AI agent architecture, tool calling, workflow orchestration, and state management.\nExperience designing reliable multi-step AI workflows with appropriate error handling and validation.\n\nEvaluation and Optimization: \nExperience evaluating LLM outputs and improving application quality.\nUnderstanding of retrieval and response evaluation metrics.\nFamiliarity with hallucination mitigation, guardrails, and output validation.\nExperience optimizing inference latency, token usage, and application cost.\n\nPreferred Qualifications: \nExperience with fine-tuning techniques such as LoRA, QLoRA, SFT, or PEFT.\nFamiliarity with Hugging Face Transformers and open-source model deployment.\nKnowledge of model quantization and inference optimization.\nExperience with Docker, Kubernetes, and cloud platforms such as AWS, Azure, or GCP.\nFamiliarity with MCP (Model Context Protocol).\nExperience with LLM observability and evaluation tools.\nSkills\nAI Agents, Embeddings, Evaluation, FastAPI, Generative AI, LLM, LangChain, LangGraph, Large Language Model, LlamaIndex, Python, RAG, REST API, Reranking, Retrieval Augmented Generation, Semantic Search, Tool Calling, Vector Databases","description_format":"text","description_chars":4326,"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":["Workflow & Process Automation (RPA, BPM)","AI Consulting & Integration"],"lifecycle":[{"event":"open","at":"2026-11-05T14:35:00Z"}],"visa":[],"liveness":{"score":90,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.903,"p_room":1,"age_days":0,"expected_fill_days":14,"reasons":["seen:0","velocity","win:early"],"computed_at":"2026-11-06T05:58:05Z"},"pay":null,"html_url":"https://alion.io/job/neoqubit-llm-engineer","json_url":"https://alion.io/job/neoqubit-llm-engineer.json","meta":{"generated_at":"2026-11-06T06:07:13Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per 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Docs: https://alion.io/developers"}}