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Sahil Gupta

Junior AI Software Engineer specializing in LLM agents, RAG, and healthcare NLP

MA, U.S.ASoftware Engineer, AI1 years experienceJuniorArtificial IntelligenceFinancial ServicesHealthcare
ScreenedReferences VerifiedIdentity VerifiedStrongly Recommended

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About

Backend engineer who built an agentic LLM system for private equity/finance that answers questions over enterprise contracts and documents using a vector-db RAG pipeline. Differentiator is a trust-focused citation framework (with highlighted source text) to reduce hallucinations in high-stakes workflows, plus strong DevOps experience deploying microservices on Kubernetes with Helm/GitOps and building Kafka real-time pipelines.

Experience

Software Engineer, AIAltius
Software Engineer Intern, Computer VisionAltius
Graduate ResearcherUMass Amherst BioNLP Lab
Graduate ResearcherMendel.ai

Education

University of Massachusetts Amherstmaster, Computer Science (2025)
University of Massachusetts Amherstbachelor, Computer Science (2023)

Key Strengths

  • Designed and owned agentic LLM backend architecture for enterprise workflows
  • Built robust RAG pipeline backed by a vector database to ground responses
  • Implemented citation/traceability framework with source linking and highlighted evidence to reduce hallucinations and increase user trust
  • Built CI/CD with GitHub Actions including automated tests, validation, performance testing, and image builds
  • Deployed containerized microservices to Kubernetes with rolling updates, namespaces, and Helm-managed configs
  • Built Kafka-based real-time pipeline handling burst traffic with partitioning and ensuring exactly-once processing via offsets and idempotent writes
  • Planned phased infrastructure migrations with dependency mapping, risk analysis, and production-mirroring staging validation
  • Built and deployed production LLM/RAG system for enterprise document/contract Q&A
  • Designed transparency features (citations + highlighted source text) to drive trust and adoption in finance/high-stakes use cases
  • Integrated structured and unstructured enterprise data via robust ETL for unified conversational querying
  • Optimized RAG for low-latency, accurate, grounded responses (indexing/retrieval tuning + domain fine-tuning)
  • Strong agent/workflow engineering using modular components, retries/fallbacks, and production monitoring
  • Rigorous evaluation approach: edge-case testing, domain benchmarks, and LLM-as-judge scoring

Reference Highlights

Strongly Recommended
  • Extensive Python backend and infrastructure experience
  • Strong backend architecture and design capability
  • Proven ability to migrate platforms to new paradigms (agentic)
  • Builds maintainable, well-documented infrastructure (simplicity and ease of maintenance)
  • Effective in complex infrastructure/migration work (containerized, on-prem)
  • Proactive in addressing unclear/changing requirements
  • Strong cross-team and client communication
  • Thrives in fast-paced startup environment
  • Keeps up with latest breakthroughs and shares with team
  • Hands-on and willing to take ownership across logistics and coordination
  • Passion and enthusiasm for high-impact tools
  • Works well under intensive, around-the-clock demands with global clients
  • Spearheaded agentic transformation of in-house document intelligence tooling
  • Strong ability to simplify complex technical decisions for non-technical stakeholders
  • Effective at communicating blockers
  • Explains technical concepts clearly without unnecessary jargon
  • Communicates doubts clearly, enabling effective collaboration and avoiding miscommunication

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Contact

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Languages

English

Skills

PythonTypeScriptJavaScriptKotlinJavaSQLC++LinuxMongoDBPostgreSQLMySQLAWSMicrosoft AzureGoogle Cloud Platform (GCP)Docker