{"id":2079135,"url":"https://alion.io/job/brillio-lead-aiml-engineer-r01572495","title":"Lead AI/ML Engineer - R01572495","company":{"id":3063,"name":"Brillio","domain":"brillio.com","url":"https://alion.io/company/brillio","size_band":"501-1000","is_staffing_agency":false,"employer_type":"services","is_intermediary":false,"listed_via":null,"ats_vendor":"Lever","truth_index":{"grade":"B","score":76,"open_postings":43,"ghost_share":0,"stale_share":0.953,"repost_share":0,"time_to_fill_p50_days":30,"computed_at":"2026-10-29T05:49:05Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"lead","employment_type":null,"work_mode":"hybrid","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":22000,"max_usd":58000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":47},"experience_years_min":4,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agentic Workflows","optional":false},{"name":"AI Agents","optional":false},{"name":"AutoGen","optional":false},{"name":"Azure","optional":false},{"name":"BentoML","optional":false},{"name":"Evidently AI","optional":false},{"name":"Function Calling","optional":false},{"name":"Great Expectations","optional":false},{"name":"Hybrid Search","optional":false},{"name":"Keras","optional":false},{"name":"Kubeflow","optional":false},{"name":"LangChain","optional":false},{"name":"LangGraph","optional":false},{"name":"LLM","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"Multi-Agent Systems","optional":false},{"name":"OpenAI","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"RAG","optional":false},{"name":"Semantic Kernel","optional":false},{"name":"SharePoint","optional":false},{"name":"TensorFlow","optional":false},{"name":"AWS","optional":true},{"name":"Azure AKS","optional":true},{"name":"Kubernetes","optional":true},{"name":"Machine Learning","optional":true},{"name":"SAS","optional":true},{"name":"SPSS","optional":true}],"status":"live","first_seen_at":"2026-10-08T09:23:14Z","employer_posted_date":"2026-10-08","last_verified_at":"2026-10-29T19:49:26Z","board_verified":true,"closed_at":null,"days_open":21,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":21},"description":"Lead AI/ML Engineer\nJob requirements\nExperience Range: With at least 4 to 6 years of experience designing, building, and operationalizing enterprise-scale AI platforms, including hands-on expertise in agentic AI, LLMs, and Azure-based solutions. Key Responsibilities:\nDesign, build, and deploy AI agents and multi-agent systems using Azure AI services, Azure OpenAI, and modern agentic frameworks such as Semantic Kernel, LangChain, LangGraph, and AutoGen.\nDevelop and operationalize agentic workflows for business functions, integrating AI solutions with Microsoft 365, Teams, SharePoint, Dynamics 365, Power Platform, and enterprise APIs.\nImplement enterprise RAG solutions utilizing Azure AI Search, vector search, hybrid search, and semantic ranking to enhance knowledge retrieval and business decision-making.\nBuild production-ready AI applications leveraging LLMs, RAG pipelines, tool/function calling, memory systems, and workflow orchestration for scalable, secure, and reliable enterprise deployment.\nEstablish observability, guardrails, responsible AI controls, evaluation, security, and monitoring for AI applications in production environments.\nOptimize agent and LLM applications for latency, accuracy, reliability, scalability, security, and cost, applying advanced techniques and metrics.\nCollaborate with cross-functional teams to identify AI opportunities, rapidly prototype solutions, and iterate based on user feedback.\nContribute to internal best practices around agent architecture, prompting, RAG, model selection, evaluation, and AI engineering standards.\nRequired Skills:\nHands-on experience with Azure AI services, Azure OpenAI, and Azure AI Foundry\nExpertise in agentic frameworks (Semantic Kernel, LangChain, LangGraph, AutoGen)\nLLM application development and prompt engineering\nEnterprise RAG architectures and vector search technologies\nIntegration with Microsoft 365, Teams, SharePoint, Dynamics 365, Power Platform, and APIs\nPython programming for AI/ML solutions\nML frameworks (TensorFlow, PyTorch, Sci-Kit Learn, Keras)\nAI workflow orchestration tools (KubeFlow, BentoML)\nModel evaluation and observability tools (Evidently AI, Great Expectations)\nAI security and governance on 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