{"id":3262574,"url":"https://alion.io/job/whilter-ai-aiml-engineer-agentic-frameworks","title":"AI/ML Engineer - Agentic Frameworks","company":{"id":3800744,"name":"Whilter AI","domain":"whilter.ai","url":"https://alion.io/company/whilter-ai","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","Gurgaon, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":23000,"max_usd":48000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":41},"experience_years_min":6,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Azure","optional":false},{"name":"Databricks","optional":false},{"name":"Google AI Studio","optional":false},{"name":"LangChain","optional":false},{"name":"LLM","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"Machine Learning","optional":false},{"name":"Multi-Agent Systems","optional":false},{"name":"OpenAI","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Semantic Kernel","optional":false}],"status":"live","first_seen_at":"2026-10-26T06:09:28Z","employer_posted_date":null,"last_verified_at":"2026-10-26T06:09:28Z","board_verified":false,"closed_at":null,"days_open":5,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":5},"description":"AI/ML Engineer (Agentic Frameworks Specialist)\n\nThe AI/ML Engineer will drive the next-generation intelligent agent ecosystem for the company. Operating within the Azure AI Foundry (Agent Factory), this role leverages modern engineering skills to wrap migrated data fabrics into context-aware agents. You will design advanced multi-agent orchestrations, manage programmatic LangChain paths, and build reliable vector indexing pipelines.\n\nRole Details:\n\nPositions Available: 1\n\nAI Architecture: Azure AI Foundry / Agent Factory, OpenAI LLM Integration\n\nOrchestration Systems: LangChain, Agentic Multi-Agent Frameworks, Vector DB Indexing\n\nKey Responsibilities:\n\n- Develop and deploy production-ready agentic architectures utilizing the Azure AI Foundry / Agent Factory environment to serve domain-specific needs.\n\n- Construct resilient orchestration paths using LangChain and advanced multi-agent frameworks, enabling complex, multi-turn reasoning and tool-calling capabilities.\n\n- Integrate and fine-tune system prompts, semantic templates, and contextual behaviors leveraging advanced OpenAI foundational models.\n\n- Build high-performance, real-time context retrieval paths connecting Azure AI Search vector databases with curated Databricks Silver layer inputs.\n\n- Implement evaluation guardrails, tracking prompt injection risks, drift metrics, and system response latency across execution nodes.\n\nTechnical Requirements:\n\n- Software engineering foundations with advanced coding skills in Python, focused on modular design, asynchronous patterns, and testing discipline.\n\n- Practical experience building systems using LangChain, Semantic Kernel, or equivalent agentic and multi-agent interaction frameworks.\n\n- Hands-on execution experience with Azure AI Foundry (formerly Azure AI Studio) or similar enterprise cloud LLM orchestration layers.\n\n- Familiarity with vector database paradigms, embedding space configurations, and context injection pipelines (RAG).\n\n- Ability to collaborate across data teams to ingest, structure, and exploit clean business domain data safely within automated inference loops.\n\nSkills\nArtificial Intelligence, Machine Learning, Agentic AI, Python, LangChain, Generative AI, Azure, RAG, Prompt 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