Headline

Software Developer, Fidelity Investments

About

Backend engineer with 2 years building distributed, cloud-native systems in financial services, and a growing focus on the backend side of AI. At Fidelity Investments, I’m part of the cloud modernization of Recordkeeping, replacing legacy mainframe brokerage systems with Java, Spring Boot, and Kafka services that process 10,000+ transactions per second. My work spans transaction capture pipelines, resilient services with retries and active-active failover, reconciliation systems that validate legacy output against cloud-native output during migration, and Python-based AWS Lambda/Batch/EMR workflows for large-scale data processing. Outside work, I build AI backends end to end: a document intelligence and retrieval system (async PDF ingestion, RAG, vector search, an MCP server, FastAPI, Claude API), and a GraphRAG investigation system over the Enron email corpus that surfaces fraud narratives across many emails instead of scoring them one by one, designed with air-gapped, on-prem constraints in mind. I care most about systems where reliability and correctness matter: financial data, auditability, and agentic pipelines whose answers can be traced back to evidence. Core stack: Java, Python, Spring Boot, FastAPI, Kafka, AWS, Kubernetes, MCP, RAG.

Location

Bengaluru

AI stack

anthropic apis

claude code

mcp

githubcopilot

Chroma

Microsoft Copilot

Work experience

Software Developer at Fidelity Investments, Jan 2024 - Present · 2 yrs 10 mos, Bengaluru, Karnataka, India, • Contributed to Fidelity’s large-scale cloud modernization initiative by developing distributed backend services to replace legacy mainframe brokerage systems within the Recordkeeping domain. • Developed high-throughput transaction capture services using Java, Spring Boot, and Kafka, processing 10,000+ transactions per second for downstream recordkeeping, balance computation, transaction history, and tax processing. • Built resilient backend services with retry mechanisms, exception handling, latency monitoring, and active-active failover support, plus reconciliation services validating legacy and cloud-native outputs during phased migration. • Developed Kafka-based ingestion pipelines and sink connectors for efficient loading into Snowflake and Oracle RDS, enabling downstream analytics and defect triaging. • Developed Python-based AWS Lambda functions and backend components supporting AWS Batch and EMR workflows for large-scale brokerage data migration and processing.

Site Reliability Engineer at Fidelity Investments, Jun 2023 - Aug 2023 · 3 mos, Bangalore Urban, Karnataka, India, Built a Datadog integration submitting custom application metrics via API calls, cutting log-analysis time by 20% and extending report retention beyond the existing 30-day limit. Worked on bookkeeping-cycle applications using AWS, REST APIs, and Spring Boot.

Education

Bachelor of Technology - BTech, Computer Science, PES University

PUC, Physics, Chemistry, Mathematics and Computer Science, Deeksha Institute - India