• AI Orchestration: Design and deploy autonomous agents to automate dev processes (e.g., automated PR summaries, synthetic test data generation, and self-healing test suites). • Workflow Automation: Build and maintain complex product workflows leveraging LLMs and RAG (Retrieval-Augmented Generation) to enhance user experiences. • Infrastructure as Code (IaC): Own the cloud architecture using Terraform or Pulumi to ensure GCP resources (Vertex AI, Cloud Run, Cloud SQL) are version-controlled and reproducible. • Full-Stack Development: Maintain and evolve our dual-portal ecosystem: Backend: Node.js, Express, and TypeORM (PostgreSQL). Frontend: React (v17 & v18) using modern state management and routing (Zustand, TanStack). • DevOps Mastery: Implement robust CI/CD pipelines (GitHub Actions/Google Cloud Build) that handle both application code and AI model versioning.

• Collaborate with engineering teams on the design and implementation of solutions using LLM's • Develop, refine, and optimize prompts to ensure the highest quality and accuracy from AI models • Collaborate with product and engineering teams to integrate AI/ML models and services into our core products • Act as an AI generalist, empowering our internal teams to use AI tooling effectively • Work in a highly collaborative environment with the product and data team to explore new AI technologies • Utilize cloud platforms, particularly AWS AI services, to build, deploy, and manage AI-powered features.

• Design, develop, and deploy LLM-powered applications • Lead the definition, development, and delivery of machine learning models • Lead the testing, deployment, and ongoing maintenance of AI systems • Optimize AI systems for performance, scalability, latency, and cost • Partner with data and engineering leads to architect AI-powered systems • Establish evaluation frameworks, monitoring, and observability

• Architect and maintain AWS demo environments using services such as EC2, ECS/Fargate, Lambda, S3, RDS, DynamoDB, IAM, KMS, API Gateway, CloudWatch, and AWS Glue • Develop Python-based solutions leveraging libraries like NumPy, Pandas, Scikit-learn, and others for data processing and automation • Build and manage Terraform modules for automated provisioning, environment resets, and decommissioning • Integrate AWS GenAI services (Bedrock, SageMaker) for real-time demo enrichment and scenario automation • Collaborate with Demo COE and Product SMEs to design and implement custom demo flows • Implement RBAC, feature toggles, and configuration management using AWS Systems Manager and AppConfig • Ensure environmental health through automated monitoring, alerting, and load testing (CloudWatch, ALB, X-Ray) • Support automated QA gates, metrics collection, and post-demo knowledge management • Provide secondary support for data engineering tasks (AWS Glue, Redshift, Athena) for ingestion and transformation • Contribute to hybrid cloud demos and integrations with Azure as needed