Open to opportunities

Praharsha srikar Kadambari

@praharshasrikarkadam1

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Backend-focused full stack engineer building scalable distributed systems.

United States

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What I'm looking for

I seek roles building scalable backend and ML-driven infrastructure, with collaborative teams, strong DevOps practices, and opportunities to optimize system performance and reliability.

I am a backend-focused full stack engineer with strong expertise in Java, Go, Python, Spring Boot, and AWS, experienced in building and optimizing large-scale distributed systems and ML-driven backend infrastructure.

I have delivered production services at scale—improving transaction throughput, optimizing query performance, and reducing deployment failures—by unifying microservices, data pipelines, and automation using Docker, Kubernetes, Terraform, Jenkins, and GitHub Actions.

I lead practical engineering solutions that combine observability, security (OAuth 2.0, JWT, RBAC), and cost-efficient auto-scaling, and I enjoy collaborating with cross-functional teams to align architecture with business and compliance goals.

Experience

Work history, roles, and key accomplishments

Current

Software Engineer

Current

JPMorgan Chase

Feb 2025 - Present (1 year 4 months)

Developed full-stack banking services using Java, Spring Boot, and React, improving transaction throughput by 30% and reducing deployment failures by 20% through microservice refactoring and CI/CD automation.

Java Spring Boot React AWS PostgreSQL OAuth 2.0 JWT Jenkins GitHub Actions

M.S. Computer Science

University of North Carolina at Charlotte

Aug 2023 - Dec 2024 (1 year 4 months)

Completed graduate studies with a focus on distributed systems and ML-driven backend infrastructure, graduating with a 3.63 GPA and hands-on projects in scalable backend and AI systems.

Distributed Systems Machine Learning TensorFlow Spark Hive AWS

Software Engineer

Cognizant

Jun 2021 - Jul 2023 (2 years 1 month)

Built Go-based backend services and gRPC integrations with Docker/Kubernetes deployments, improving API response efficiency by 25% and enhancing observability with Prometheus and Grafana.

Go gRPC Docker Kubernetes Prometheus Grafana SQL OAuth 2.0 RBAC

Education

Degrees, certifications, and relevant coursework

University of North Carolina at Charlotte

Master of Science, Computer Science

2023 - 2024

Grade: 3.63/4.00

Completed a Master of Science in Computer Science with coursework and projects focused on distributed systems, backend engineering, and ML-driven infrastructure; graduated with a 3.63 GPA.