Daniel Schultz

Led the development of high quality, and reliability product, providing innovative solutions for startups in the 0-1 and 1-10 growth stage.

• Designed and delivered an AI-powered healthcare workflow automation solution for enterprise healthcare clients, enabling AI agents to assist with clinical document processing, patient information retrieval, and administrative task automation using Python, FastAPI, LangChain, RAG, Agentic AI, MCP, and secure integration with healthcare systems through REST APIs and HL7 FHIR interfaces.

• Built an AI agent-driven legal product for enterprise legal teams, automating contract review, clause extraction, compliance checks, and document analysis by integrating LLMs, LangChain orchestration, vector databases, and enterprise knowledge sources while implementing human-in-the-loop approval workflows for high-risk decisions.

• Designed and deployed a startup-style MVP for AI-powered Marketing product using Python, Django, Typescript, React, React Native and Next.js, providing domain-specific answers from internal policy documents.

• Developed Python(FastAPI) and Javascript(Node.js) microservices - containerized within Docker and Kubernetes for automation platform, integrating with Kafka event streams and GraphQL APIs.

• Implemented multi-environment pipelines using Jenkins, Terraform, and GitHub Actions, automating test suites and cloud provisioning on AWS and GCP.

• Implemented event-driven data workflows with Pub/Sub and AWS Kinesis, integrating real-time messages from enterprise systems into analytics pipelines on BigQuery and Snowflake.

• Experience in using Cursor / Github Copilot to speed up development process

Shipped their research engine from zero stage, and led multiple fund rounds

• ResearchCoin Rewards Engine: Maintained and optimized Python / Django backend APIs managing token transactions, built REST endpoints for community reward flows.

• Hub Discovery Portal: Developed React + Redux, React Native front-end with Python Flask services to display trending hubs, top discussions, and author analytics.

• Research Import Pipeline: Designed Python ETL jobs for importing and normalizing content from arXiv, PubMed, and bioRxiv, storing metadata in PostgreSQL.

• Notification & Activity Feed: Built microservices in Python with Socket.IO and AWS SNS to push real-time updates to users.

• Developed Python microservices for vibration data analysis (FFT / signal processing), integrated results into internal tooling.

• Designed Node.js REST APIs and AWS Lambda functions to automate part tracking and supplier synchronization with SAP systems.

• Created an analytics dashboard using MERN to allow marketing managers to check user activities in real time.

• Integrated IoT analytics pipelines with Google Cloud Pub/Sub and BigQuery, enabling large-scale vibration data aggregation and predictive insights.