I’m a software engineer who builds cloud-native, distributed systems and AI-powered applications, with a strong focus on production reliability. I’ve worked across Java/Spring microservices, REST/gRPC APIs, event-driven architectures, and AWS-based data pipelines—designing systems that handle real workload and recover gracefully from failures. I also enjoy developing end-to-end AI features like RAG pipelines and ML inference workflows, including retrieval and evaluation, orchestration with Kafka/workers, and performance tuning. From API governance to containerized deployments on Kubernetes, I bring a practical, developer-friendly approach to shipping maintainable services and delivering measurable improvements.…

Rajat Gade

I’m a software engineer who builds cloud-native, distributed systems and AI-powered applications, with a strong focus on production reliability. I’ve worked across Java/Spring microservices, REST/gRPC APIs, event-driven architectures, and AWS-based data pipelines—designing systems that handle real workload and recover gracefully from failures. I also enjoy developing end-to-end AI features like RAG pipelines and ML inference workflows, including retrieval and evaluation, orchestration with Kafka/workers, and performance tuning. From API governance to containerized deployments on Kubernetes, I bring a practical, developer-friendly approach to shipping maintainable services and delivering measurable improvements.…

Available to hire

I’m a software engineer who builds cloud-native, distributed systems and AI-powered applications, with a strong focus on production reliability. I’ve worked across Java/Spring microservices, REST/gRPC APIs, event-driven architectures, and AWS-based data pipelines—designing systems that handle real workload and recover gracefully from failures.

I also enjoy developing end-to-end AI features like RAG pipelines and ML inference workflows, including retrieval and evaluation, orchestration with Kafka/workers, and performance tuning. From API governance to containerized deployments on Kubernetes, I bring a practical, developer-friendly approach to shipping maintainable services and delivering measurable improvements.

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Skills

Experience Level

Java
Expert
Spring
Expert
JavaScript
Expert
Python
Expert
API
Expert
TypeScript
Expert
SQL
Expert
Redis
Expert
PostgreSQL
Expert
Docker
Expert
AWS
Expert
Kubernetes
Expert
React JS
Expert
MongoDB
Expert
GraphQL
Expert
Go
Expert
Prompt Engineering
Expert
Django
Expert
Tailwind
Expert
GitHub Copilot
Intermediate
C++
Intermediate
Jira
Intermediate
AI Data Labelling
Intermediate
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Language

English
Fluent

Work Experience

Software Engineer (Contract, Remote) at R anco Labs
February 1, 2026 - July 31, 2026
Architected and developed Java 17 and Spring Boot microservices with REST/gRPC APIs for an internal payment operations and exception management platform supporting reconciliation, case investigation, and transaction lifecycle workflows. Engineered Kafka event streams for payment status, settlement, and exception workflows while processing 80K+ events per hour with per-transaction ordering and recoverability via partition keys, retries, and dead-letter handling. Containerized Spring Boot services with Docker and deployed to Kubernetes using Helm and GitHub Actions; standardized readiness checks and deployment templates that reduced failed deployments from 9% to 3% and rolled back faster (18 to 9 minutes). Established API governance using OpenAPI 3.0, schema versioning, and gRPC contracts to enable backward-compatible integrations across 10+ internal services.
Software Engineer at Ranco IT
January 31, 2026 - Present
Shipped checkout microservices with comprehensive telemetry and distributed tracing, enabling proactive detection of gateway bottlenecks and reducing MTTR for production incidents. Engineered resilient API gateway configurations implementing intelligent rate-limiting and circuit-breaking patterns to protect downstream payment services during traffic spikes.
Software Engineer (Research) at UMass Amherst
February 1, 2025 - January 1, 2026
Built an end-to-end AI-native application (React, FastAPI) with real-time streaming interfaces, reducing conversational latency and delivering a highly responsive user experience. Designed and deployed agentic workflows enabling autonomous multi-step user tasks while maintaining session state across concurrent interactions. Iterated on product features through rapid prototyping and user feedback, improving response quality and usability. Instrumented the full stack with Prometheus and Grafana to establish telemetry and rapidly detect/resolve latency bottlenecks across frontend and ML services.
Associate Software Engineer at Accenture
July 27, 2021 - January 30, 2023
Developed Spring Boot backend modules with optimized SQL schemas, supporting 5K+ daily transactions at 99.9% uptime and delivering 18% faster response times across multi-region deployments; implemented Redis caching layers with concurrent-safe pipelines, reducing database load and request latency by 15% and improving checkout responsiveness during traffic spikes; increased automated test coverage from 70% to 90%, reducing production defects by 30% and stabilizing cross-team releases; designed versioned catalog entities and APIs, reducing downstream integration time by 20% and accelerating feature delivery through backward-compatible schema evolution.
Software Engineer at Accenture
January 1, 2021 - January 1, 2023
Built enterprise-scale Java/Spring Boot microservices and REST APIs supporting checkout, payments, and transactional workflows in distributed systems serving 50K+ concurrent users. Reduced p95 API latency by 30% through SQL query tuning, caching, and optimized data access patterns. Integrated external payment gateways via REST APIs with retries, idempotency, and failure handling, supporting $10M+ transaction volume during the engagement. Improved scalability during seasonal traffic spikes by introducing Redis caching and optimizing database access patterns, reducing repeated database reads across high-traffic checkout workflows. Investigated production payment failures using application logs and transaction audit trails, resolving integration issues and contributing JUnit/Mockito regression coverage to prevent recurrence.

Education

Master of Science in Computer Science at University of Massachusetts Amherst
February 1, 2023 - January 1, 2025
Bachelor of Engineering in Computer Engineering at Savitribai Phule Pune University
July 1, 2017 - April 1, 2021
Master of Science - Computer Science (GPA: 3.87/4) at University of Massachusetts Amherst
February 1, 2023 - January 1, 2025
Bachelor of Engineering - Computer Engineering (GPA: 9.2/10) at Pune University
July 1, 2017 - April 1, 2021

Qualifications

Add your qualifications or awards here.

Industry Experience

Computers & Electronics, Software & Internet, Professional Services, Media & Entertainment, Financial Services
    Aegis: Telemetry & Fallback API Gateway
    • Built a self-healing API gateway for agentic workflows and LLM-powered applications using Python and FastAPI for reliable AI-driven user interactions despite upstream failures.
    • Architected a semantic caching layer utilizing Redis and local embedding models to intercept high-similarity queries, bypassing costly LLM inference entirely and heavily reducing p99 response latency.
    • Orchestrated LLM infrastructure to support continuous AI-driven interactions, specifically engineering fallbacks to handle edge cases like rate-limiting and external API downtime.
    • Engineered and orchestrated LLM infrastructure, including fallbacks for AI-driven interaction edge cases like rate-limiting and API downtime.
    • Instrumented the gateway with rigorous Prometheus and Grafana telemetry to monitor cache hit rates and
      system degradation, deploying data quality gates to reject prompt injection anomalies automatically.