{"id":4045658,"url":"https://alion.io/job/pragma-edge-artificial-intelligence-engineer","title":"Artificial Intelligence Engineer","company":{"id":2939282,"name":"Pragma Edge","domain":"pragmaedge.com","url":"https://alion.io/company/pragmaedge","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"],"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":"AutoGen","optional":false},{"name":"AWS","optional":false},{"name":"AWS Bedrock","optional":false},{"name":"CI/CD","optional":false},{"name":"CrewAI","optional":false},{"name":"Fine-tuning","optional":false},{"name":"Gemini","optional":false},{"name":"LangGraph","optional":false},{"name":"LLM","optional":false},{"name":"Mistral","optional":false},{"name":"Multi-Agent Systems","optional":false},{"name":"NLP","optional":false},{"name":"OpenAI","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"PyTorch","optional":false},{"name":"RAG","optional":false},{"name":"Azure","optional":true},{"name":"FAISS","optional":true},{"name":"LangChain","optional":true},{"name":"Pinecone","optional":true},{"name":"Python","optional":true},{"name":"TensorFlow","optional":true},{"name":"Weaviate","optional":true}],"status":"live","first_seen_at":"2026-11-10T23:35:45Z","employer_posted_date":null,"last_verified_at":"2026-11-10T23:35:45Z","board_verified":false,"closed_at":null,"days_open":0,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":0},"description":"We are looking for a Senior AI Engineer with proven experience in Agentic AI, Large Language Models (LLMs), and advanced NLP systems. The candidate will take end-to-end ownership of multi-agent architectures, from design and development through production deployment and optimization.\n\nKey Responsibilities:\nAgentic AI & Multi-Agent ArchitectureDesign and implement agent-based and multi-agent systems using frameworks such as CrewAI, LangGraph, AutoGen, and LangChain\nBuild autonomous agents capable of planning, reasoning, tool usage, and long-running task execution\nIntegrate LLMs with tools, APIs, memory stores, vector databases, and RAG pipelines\n\nLLM Development & OptimizationFine-tune and optimize foundation models (e.g., Mistral, Gemini Flash, OpenAI models, AWS Bedrock)\nDevelop advanced prompt strategies and control loops for agent reasoning\nBuild NLP pipelines for summarization, classification, QA, and text generation\n\nProduction Deployment & ScalabilityDeploy AI services and agent workflows to production environments\nOptimize solutions for latency, cost, memory usage, and scalability\nCollaborate with DevOps and platform teams on CI/CD, monitoring, and reliability\n\nEvaluation, Safety & ReliabilityImplement evaluation frameworks for LLM and agent performance\nEnsure robustness, observability, and responsible AI deployment\nApply AI safety, ethical AI, and governance best practices\n\nCross-Functional CollaborationWork closely with product, research, data engineering, and software teams\nTranslate business requirements into scalable AI solutions\nMentor junior engineers and contribute to design reviews\n\nDocumentation & Knowledge SharingMaintain detailed technical documentation\nCommunicate system design, trade-offs, and outcomes to stakeholders\n\nRequired Qualifications:\nBachelor's or Master's degree in Computer Science, AI, Data Science, or related fields\n3-5 years of hands-on experience in AI/ML or applied NLP\nStrong proficiency in Python\nExperience with PyTorch and/or TensorFlow\nHands-on experience with LLMs, prompt engineering, fine-tuning, and RAG\nPractical exposure to agentic AI and multi-agent orchestration\nExperience building scalable, distributed systems\nStrong problem-solving and communication skills\n\nPreferred / Nice-to-Have Skills:\nExperience with WatsonX, LangChain, AutoGen, LangGraph, CrewAI\nCloud platforms: IBM Cloud, AWS, Azure, or GCP\nExperience with vector databases (FAISS, Pinecone, Weaviate, etc.)\nContributions to open-source AI projects\nKnowledge of AI safety, alignment, and ethical AI principles\nSkills\nLLM, LLMs, Large Language Models, PyTorch, Python, TensorFlow","description_format":"text","description_chars":2624,"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":["Integration & API 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