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Sayali Gedam

Mid-level Backend Software Engineer specializing in Python microservices

JPMorgan ChaseNew England CollegeBoston, MA5 Years ExperienceMid LevelWorks On-Site

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About

Backend/platform engineer who has owned end-to-end production systems in financial/claims domains, including a transaction analytics microservice platform processing ~10M daily operations and cutting latency from ~150ms to <70ms. Also productionized an LLM-powered monitoring/alerting capability (Llama 3 + FastAPI) with prompt design, guardrails, and production evaluation, and led monolith-to-microservices modernization on AWS using feature flags and parallel runs.

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Key Strengths

  • Owned end-to-end production microservice platform (backend, data, infra) processing ~10M daily operations
  • Reduced transaction latency from ~150ms to <70ms via PostgreSQL query optimization and Redis caching
  • Built automated CI/CD with GitHub Actions and Pytest to enable safer deployments
  • Implemented production monitoring/observability with Prometheus + Grafana and improved incident response
  • Productionized LLM-based monitoring/alerting (Llama 3 + FastAPI) with structured prompts, guardrails, and evaluations
  • Led incremental legacy modernization from monolith to FastAPI microservices on AWS (Lambda/ECS) using parallel runs and feature flags
  • Strong cross-functional execution across backend/DevOps/data with minimal oversight; prioritizes and ships in small deliverables
  • Stakeholder management: translated ambiguous leadership goals into a metrics-driven roadmap and iterated via demos/feedback loops

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Experience

Software EngineerJPMorgan Chase & Co. · Jul 2024 – Present
Software EngineerUnitedHealth Group · Jul 2023 – Jun 2024
Software Developer AssociateR-Financial · Sep 2018 – Aug 2021

Education

New England Collegemaster, Computer Science (2023)
G H Raisoni College of Engineeringbachelor, Electronics Engineering (2020)

Languages

English

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Connect with Sayali

Sayali already has a relationship with Reval, so a warm intro from us gets a much better response than cold outreach.

Typically responds within 24 hours

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Sayali GedamMid-level Backend Software Engineer specializing in Python microservices