• Design and implement AI workflows on top of existing data pipelines (product feedback extraction, customer update generation, onboarding plans, win/loss summaries, CRM enrichment) • Extend and refine the current TypeScript-based agent: tooling, tool schemas, routing logic, error handling, and observability • Improve transcript and account matching across Zoom, Granola, and Salesforce using entity resolution, heuristics, and/or LLM-assisted matching • Integrate new data sources (Slack, Zendesk, Google Drive, Nexus/telemetry, email) into the existing AWS stack • Define and consume pre-aggregated account/opportunity summaries in S3 for fast, reliable query • Optimize Lambda-based data processing jobs for cost, reliability, and performance • Iterate on model strategy: cheap routing (e.g., Claude Haiku) vs. higher-quality response models (e.g., Claude Sonnet/Opus) • Evaluate prompts, tool selection quality, and response accuracy with clear metrics • Collaborate with GTM stakeholders (Sales, SE, CS, Product, Marketing) to define, test, and refine AI-assisted workflows • Partner with infra engineering (Terraform, Kubernetes) to ensure deployment, security, and observability are production-ready • Contribute to future UI/UX (Slack bot flows, simple web UI/dashboards) to expose workflows to end users