• 8+ years of experience in software/data architecture with 3+ years in AI/ML, including hands-on work with generative AI solutions.
• Proven experience designing and deploying AI workflows using:
• AWS: Amazon Bedrock, SageMaker, Lambda, DynamoDB, OpenSearch.
• Azure: Azure OpenAI, Azure ML, Azure Cognitive Services, Cognitive Search.
• Expertise in RAG pipeline architecture, prompt engineering, and vector database design.
• Familiarity with tools and frameworks for AI agent orchestration (e.g., LangChain, Semantic Kernel, AWS Agent Framework).
• Strong understanding of cloud security, identity management (IAM, RBAC), and compliance in enterprise environments.
• Proficiency in Python and hands-on experience with modern ML libraries and APIs used in AWS and Azure.

Preferred Qualifications:

• Experience working with LLMOps tools in cloud environments (e.g., model monitoring, logging, performance tracking)
• Understanding of fine-tuning strategies, model evaluation, and safety/risk management of GenAI models.
• Familiarity with serverless architecture, containerization (ECS, AKS), and CI/CD practices in AWS/Azure.
• Ability to translate business problems into scalable AI solutions with measurable outcomes.