Vetted Software Development Engineers in the Bangalore Metro

“Candidate has developed a disciplined AI-first engineering workflow that combines design docs, prior PR analysis, testing plans, and multi-agent coordination to accelerate delivery without sacrificing quality. They described acting as a tech lead for AI agents, overseeing code structure, business logic, testing, and service contracts, and reported reducing manual coding effort by nearly 80%.”

Anandapadmanabhan Santhosh

Screened

Junior Software Engineer specializing in distributed systems and backend microservices

Bangalore, India1y exp

“Distributed systems engineer (ex-Nykaa, Licious) who built a PBFT-based Byzantine fault-tolerant consensus system in Go for a multi-node banking-style application, including checkpointing and automated failover/leader election. Strong production reliability background with Docker, Jenkins CI/CD, and monitoring/on-call troubleshooting using Grafana and New Relic; no direct ROS/robotics hardware experience yet but has highly transferable multi-node coordination expertise.”

Aman Kushwaha

Screened

Senior Frontend Engineer specializing in React, Next.js, and FinTech UI architecture

Bangalore, India4y exp

“Frontend/product engineer with strong ownership across architecture, deployment, and cross-functional product decisions, especially in finance workflow systems. Built a metadata-driven React/TypeScript framework at Hyperbots that cut feature development effort by ~70% and manual effort by 50%+, and has also driven backend API cleanup, real-time experiences, and a full GA4 tracking architecture redesign.”

Yuvraj Singh Chauhan

Screened

Entry-level AI/ML Engineer specializing in LLMs, RAG, and DevOps automation

Bangalore, India1y exp

“Built and owned a production-scale AI-driven software release/version intelligence platform orchestrated via GitHub Actions that tracks 1000+ upstream repositories and automatically generates SLA-bound JIRA upgrade tickets for hardened container images. Replaced brittle regex/PEP440 parsing with an LLM-based semantic filtering layer plus deterministic validation to handle noisy/inconsistent GitHub tags at scale, with monitoring for coverage, latency, and correctness validated against upstream ground truth.”

“Backend engineer who built and launched a warehouse locations/inventory microservice for Walmart, supporting a new product rollout with on-call war-room ownership and now running across all US distribution centers. Emphasizes reliability and correctness (background syncs, 2PC concepts, alerting) plus design-first API development in Python/FastAPI with OAuth/JWT and RBAC, and has led staged legacy-to-microservice migrations with continuous data integrity verification.”

Mahiyadav Sidda

Screened

Junior Machine Learning Engineer specializing in LLMs, RAG, and on-device AI

Bangalore, India2y exp

“Built an "Offline Study Assistant" that runs LLM inference locally on a 5-year-old Android device using Llama.cpp and the Android NDK, achieving a 27x speedup and cutting time-to-first-token from 11 minutes to 30 seconds. Also has applied backend/API experience with FastAPI, Supabase (Auth + RLS), and production hardening of a RAG system at Hashmint using Celery and Redis to eliminate PDF-processing-related query failures.”

Pawan Tiwari

Screened

Senior Frontend Engineer specializing in real-time data and AI-powered interfaces

Bangalore, India5y exp

“Frontend-leaning product engineer who repeatedly operates across the stack, from React/TypeScript architecture to backend eventing, caching, and real-time systems. They describe measurable wins in high-scale operational products—cutting invoice download time by ~99%, stabilizing 100k+ daily-query dashboards to 200ms, and building internal platform tooling including an AI infrastructure agent adopted by 50+ engineers.”

“Software engineer actively using AI-first development workflows, including Cursor, prompt engineering, and multi-agent setups, to dramatically compress development time. Most notably, they say they built a Regression Optimizer product end-to-end from scratch and used multi-agent approaches to improve troubleshooting and response quality.”