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Lead AI/ML Engineer - R01572495

Brillio-2
Bengaluru, IND
Lead · 4–6 years experience
Discovered 2 weeks ago
awsazureazure-functionsdynamics-365keraskubeflow

Full Job Posting

Job requirements

  • Experience 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.
  • 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.
  • Hands-on experience with Azure AI services, Azure OpenAI, and Azure AI Foundry
  • Expertise in agentic frameworks (Semantic Kernel, LangChain, LangGraph, AutoGen)
  • LLM application development and prompt engineering
  • Enterprise RAG architectures and vector search technologies
  • Integration with Microsoft 365, Teams, SharePoint, Dynamics 365, Power Platform, and APIs
  • Python programming for AI/ML solutions
  • ML frameworks (TensorFlow, PyTorch, Sci-Kit Learn, Keras)
  • AI workflow orchestration tools (KubeFlow, BentoML)
  • Model evaluation and observability tools (Evidently AI, Great Expectations)
  • AI security and governance on Azure
  • Design, 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.
  • Develop and operationalize agentic workflows for business functions, integrating AI solutions with Microsoft 365, Teams, SharePoint, Dynamics 365, Power Platform, and enterprise APIs.
  • Implement enterprise RAG solutions utilizing Azure AI Search, vector search, hybrid search, and semantic ranking to enhance knowledge retrieval and business decision-making.
  • Build production-ready AI applications leveraging LLMs, RAG pipelines, tool/function calling, memory systems, and workflow orchestration for scalable, secure, and reliable enterprise deployment.
  • Establish observability, guardrails, responsible AI controls, evaluation, security, and monitoring for AI applications in production environments.
  • Optimize agent and LLM applications for latency, accuracy, reliability, scalability, security, and cost, applying advanced techniques and metrics.
  • Collaborate with cross-functional teams to identify AI opportunities, rapidly prototype solutions, and iterate based on user feedback.
  • Contribute to internal best practices around agent architecture, prompting, RAG, model selection, evaluation, and AI engineering standards.

Key Responsibilities:

  • Design, 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.
  • Develop and operationalize agentic workflows for business functions, integrating AI solutions with Microsoft 365, Teams, SharePoint, Dynamics 365, Power Platform, and enterprise APIs.
  • Implement enterprise RAG solutions utilizing Azure AI Search, vector search, hybrid search, and semantic ranking to enhance knowledge retrieval and business decision-making.
  • Build production-ready AI applications leveraging LLMs, RAG pipelines, tool/function calling, memory systems, and workflow orchestration for scalable, secure, and reliable enterprise deployment.
  • Establish observability, guardrails, responsible AI controls, evaluation, security, and monitoring for AI applications in production environments.
  • Optimize agent and LLM applications for latency, accuracy, reliability, scalability, security, and cost, applying advanced techniques and metrics.
  • Collaborate with cross-functional teams to identify AI opportunities, rapidly prototype solutions, and iterate based on user feedback.
  • Contribute to internal best practices around agent architecture, prompting, RAG, model selection, evaluation, and AI engineering standards.

Required Skills:

  • Hands-on experience with Azure AI services, Azure OpenAI, and Azure AI Foundry
  • Expertise in agentic frameworks (Semantic Kernel, LangChain, LangGraph, AutoGen)
  • LLM application development and prompt engineering
  • Enterprise RAG architectures and vector search technologies
  • Integration with Microsoft 365, Teams, SharePoint, Dynamics 365, Power Platform, and APIs
  • Python programming for AI/ML solutions
  • ML frameworks (TensorFlow, PyTorch, Sci-Kit Learn, Keras)
  • AI workflow orchestration tools (KubeFlow, BentoML)
  • Model evaluation and observability tools (Evidently AI, Great Expectations)
  • AI security and governance on Azure

Preferred Skills:

  • Experience with Azure Functions, Azure Container Apps, Azure Kubernetes Service (AKS), and Azure Storage
  • Proficiency in R and R Studio for statistical computing
  • Knowledge of SAS or SPSS for advanced statistical modeling
  • Familiarity with microservices, event-driven architectures, and enterprise integrations
  • Expertise in developing reusable agent frameworks, prompt libraries, and deployment patterns
  • Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, or a closely related discipline
  • Certification in Machine Learning or Data Science from a recognized institution (e.g., TensorFlow Developer Certificate, AWS Certified Machine Learning Specialty, Microsoft Certified: Azure AI Engineer Associate)
  • Certification in statistical analysis tools or platforms (e.g., SAS Certified Statistical Business Analyst)

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