Headline

Software Engineer II | Backend & Distributed Systems | Java, Spring Boot, Python · Microservices, AWS, Kubernetes · Applied AI (RAG, LangGraph)

About

Backend & distributed-systems engineer with 5 years building and operating large-scale, high-availability services in production. Currently Software Engineer II at EPAM, on engagements with Uber (core infrastructure) and Goldman Sachs (financial data platform). I build Java, Spring Boot, Python, and Go services — microservices, REST/gRPC APIs, event-driven pipelines, and cloud-native systems on AWS and GCP — and own them end to end: design, CI/CD, observability, debugging, and on-call. Selected work: - Scaled subscriber-processing throughput ~66x — from ~30K records per multi-minute batch to millions in sub-minute windows — and sustained 99.99% uptime across geo-redundant, multi-cluster deployments at Sandvine. - Owned the majority of a 100+ microservice TChannel→YARPC migration across Uber's ride-handling infrastructure, with automation that lifted migration throughput ~7.5x. - Built high-volume AWS Glue/Lambda + Snowflake data pipelines for regulated financial workflows at Goldman Sachs. Core strengths: Java, Spring Boot, Python, Go, distributed systems, microservices, Kafka, AWS, Kubernetes, Redis, PostgreSQL, Snowflake, observability (Prometheus/Grafana), and performance optimization. My differentiator is applied AI built with production rigor — backend-heavy RAG systems, multi-agent workflows, and infra-diagnostic agents using FastAPI, LangChain, LangGraph, Spring AI, and pgvector. Projects include DocuMind (enterprise RAG) and InfraAgent (multi-agent DevOps assistant). Open to Senior Backend / Distributed Systems / Platform roles at product companies where I can own scalable systems end to end. 📫 aditya.bichave@gmail.com · GitHub: github.com/Aditya-Bichave

Location

Bengaluru

AI stack

antigravity

opencode

claudecode

Work experience

Software Engineer II at EPAM Systems, Jul 2024 - Present · 2 yrs 2 mos, Bengaluru, Karnataka, India, Backend and data-platform engineering on client engagements — Java, Go, Python; REST/gRPC/YARPC; AWS Glue/Lambda; Snowflake; Kafka; Kubernetes/Helm; CI/CD; distributed systems. Client: Uber — Core Infrastructure / Backend Services - Owned the majority of a 100+ microservice migration of internal service communication (TChannel→YARPC) across Go and Java services in Uber's ride-handling infrastructure — updating APIs, configs, CI/CD workflows, and monitoring paths for a reliable, incremental rollout. - Built internal scaffolding and automation that accelerated migration throughput ~7.5x, standardizing rollout across multiple teams. - Authored migration playbooks adopted org-wide, improving consistency and onboarding. Client: Goldman Sachs — Financial Data Platform (Asset Management & Reporting) - Architected high-volume Python ETL pipelines on AWS Glue/Lambda, owning ingestion → transformation → modeling → delivery for downstream analytics and reporting. - Modeled semantic data layers (Legend Studio/PURE) and tuned Snowflake queries/schemas; enforced data-quality checks for regulated financial data. - Deployed on Kubernetes/Helm with CI/CD and Kafka event streaming; instrumented Prometheus/Grafana for monitoring and alerting.

Software Engineer 2 at Sandvine, Mar 2022 - Jun 2024 · 2 yrs 4 mos

Software Engineer at Sandvine, Oct 2021 - Mar 2022 · 6 mos, Bangalore Urban, Karnataka, India

Software QA Automation Engineer at PubMatic, Jul 2021 - Oct 2021 · 4 mos, Pune Division, Maharashtra, India, - Built and tested backend service features; debugged production issues and contributed to performance and reliability improvements that fed into the platform's high-availability roadmap.

Machine Learning Research Intern at Centre for Computational Technologies (CCTech), Jun 2019 - Aug 2019 · 3 mos, Pune

eYRC-2018 at e-Yantra, IIT Bombay, Oct 2018 - Apr 2019 · 7 mos, Pune/Pimpri-Chinchwad Area, Member Of Team Qualifying for National Level E Yantra Robotics Competition 2018 HC-#4735 e-Yantra Robotics Competition (eYRC) is a unique annual competition for undergraduate students in science and colleges. Selected teams are given a robotic kit complete with accessories and video tutorials to help them learn basic concepts in Machine Learning, Deep Learning, Computer Vision, embedded systems and microcontroller programming. Abstracts of real-world problems assigned as "themes" are then implemented by the teams using the robotic kits.

Education

Bachelor's degree, Computer Engineering, Pimpri Chinchwad Education Trust'S. Pimpri Chinchwad College Of Engineering

11th-12th, Science PCM, Ashoka Universal School and Jr. College,Nashik, Maharashtra