Design and implement AI workflows on data pipelines (CRM enrichment).
Extend/refine the TS-based agent: tooling, routing, observability.
Improve transcript/account matching across Zoom/Granola/Salesforce via entity resolution.
Integrate data sources (Slack, Zendesk, Drive, Nexus) into the AWS stack.
Define and consume pre-aggregated account/opportunity summaries in S3 for fast queries.

🎯 Requirements

5+ years in software engineering, including 1-2+ years building LLM-based apps.
TypeScript/Node.js (ideal) or Python for backend and data processing.
Hands-on with LLM tool calling/agents (LangChain or equivalent).
Practical RAG: chunking, metadata schemas, retrieval, relevancy.
AWS: Lambda, S3, IAM, CloudWatch; Bedrock a plus.
Data integration/pipelines: APIs and webhooks (Salesforce, Slack, Zendesk, Zapier).

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