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.

• Architected RAG pipelines with LangChain and Pinecone, combining embeddings, metadata filtering, hybrid retrieval, and reranking to improve response grounding. 

• Designed stateful AI agents with LangGraph, orchestrating tool calls, guardrails, retries, permissions, structured outputs and human approval across enterprise workflows. 

• 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 / Claude Code to speed up development process

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

• Built and scaled ResearchHub's scientific publishing and collaboration workflows, working closely with founders, researchers, and product teams to turn early MVP concepts into production-ready features for open-access research.

• Developed full-stack features for ResearchHub's research paper discovery and publishing platform using React, Next.js, TypeScript, Python, FastAPI, PostgreSQL, Redis, and AWS S3, supporting manuscript submissions, researcher profiles, and scientific discussions.

• Engineered automated research paper ingestion pipelines using Python, OCR, REST APIs, Redis, and background workers to process scientific manuscripts, extract metadata, and organize publications from external preprint repositories.

• Applied NLP and machine-learning techniques to scientific paper classification, keyword extraction, metadata enrichment, and relevance ranking, improving research discovery and content organization across scientific disciplines.

• Built semantic search and recommendation capabilities using Elasticsearch, vector embeddings, Python, and PostgreSQL to help researchers discover relevant publications, explore related topics, and identify scientific content aligned with their interests.

• Improved reliability across ResearchHub's publishing and peer-review workflows by implementing Pytest, Playwright, GitHub Actions, and CI/CD pipelines, establishing 500+ automated test cases covering API endpoints, manuscript processing, and core user interactions.

• 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.