• Work across diverse GenAI platforms like AWS, Salesforce, Oracle, Snowflake, MS Copilot, and other 3rd party GenAI platforms and libraries. • Automate workflows involving extraction of complex, multimodal unstructured content from variety of sources in to highly accurate and reliable structured content using platforms like AWS Textract and Bedrock • Design and build MCP hosts, clients and servers • Establish and use frameworks for automated LLM testing • Create regression test suites to detect drift or prompt breakage • Integrate with internal and external web services using secure authentication and authorization mechanisms • Adopt and ensure safe practices to protect against prompt injections, jailbreaks, and conform to enterprise security guidelines • Design, develop, and deploy production-grade traditional ML models (e.g., regression, classification, clustering, recommender systems) for a variety of business use cases. • Design, maintain, and optimize end-to-end AI/ML pipelines including data ingestion, training, evaluation, deployment, and monitoring on cloud infrastructure (e.g., AWS or equivalent) • Ensure AI/ML solutions are scalable, reliable, secure, and cost-effective within cloud environments • Create reusable components, frameworks, and best practices to accelerate AI development • Partner with data scientists, architects, product managers, business stakeholders and technical teams across organization to align AI solutions with organizational goals. • Provide hands-on technical support and mentorship to technical teams across the enterprise.