21 hours ago
Bengaluru, IndiaStaff+
Responsibilities
- Design, build, and deploy AI agents and multi-agent systems using Azure AI services, Azure OpenAI, Semantic Kernel, LangChain, LangGraph, and AutoGen.
- Develop and operationalize agentic workflows integrated with Microsoft 365, Teams, SharePoint, Dynamics 365, Power Platform, and enterprise APIs.
- Implement enterprise RAG solutions using Azure AI Search, vector search, hybrid search, and semantic ranking.
- Build production-ready LLM applications with RAG pipelines, tool and function calling, memory systems, and workflow orchestration.
- Establish observability, guardrails, responsible AI controls, evaluation, security, and monitoring for production AI applications.
- Optimize AI agents and LLM applications for latency, accuracy, reliability, scalability, security, and cost.
- Collaborate with cross-functional teams to identify AI opportunities, prototype solutions, and iterate based on user feedback.
- Contribute to standards and best practices for agent architecture, prompting, RAG, model selection, evaluation, and AI engineering.
Requirements
- At least 4 to 6 years of experience designing, building, and operationalizing enterprise-scale AI platforms.
- Hands-on experience with Azure AI services, Azure OpenAI, and Azure AI Foundry.
- Expertise with Semantic Kernel, LangChain, LangGraph, and AutoGen.
- Experience developing LLM applications, prompt engineering, enterprise RAG architectures, and vector search solutions.
- Experience integrating AI solutions with Microsoft 365, Teams, SharePoint, Dynamics 365, Power Platform, and APIs.
- Python programming experience for AI and ML solutions.
- Experience with TensorFlow, PyTorch, Sci-Kit Learn, and Keras.
- Experience with KubeFlow and BentoML for AI workflow orchestration.
- Experience with Evidently AI and Great Expectations for model evaluation and observability.
- Knowledge of AI security and governance on Azure.
- Preferred experience with Azure Functions, Azure Container Apps, Azure Kubernetes Service, Azure Storage, R, R Studio, SAS, or SPSS.
- Knowledge of microservices, event-driven architectures, enterprise integrations, reusable agent frameworks, prompt libraries, and deployment patterns.
- A bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, or a related discipline is desired.
- Preferred certifications include the TensorFlow Developer Certificate, AWS Certified Machine Learning Specialty, Microsoft Certified: Azure AI Engineer Associate, or SAS Certified Statistical Business Analyst.
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About Brillio
Brillio is a privately held digital engineering and enterprise AI services firm that helps Fortune 1000 companies modernize products, data, and infrastructure. It combines consulting and managed services with an accelerator platform (ADAM) across cloud, AI, data engineering, customer experience, and infrastructure workstreams. Founded in 2014 and headquartered in Dallas, it operates delivery centers across North America, Europe, and Asia, with focus areas that include healthcare and life sciences.