---
title: "Bhawna Faujdar - Lead Software Engineer (AI Infrastructure) in Greater Bengaluru Area | Tal"
description: "Meet Bhawna Faujdar, Senior Backend Engineer | Distributed Systems, Java, Spring Boot | AI Infrastructure | Ex-Walmart, Amex based in Greater Bengaluru Area."
image: "https://tal.club/meet/bhawna-3/share-image"
---

# Bhawna Faujdar on Tal

## Headline

Senior Backend Engineer \| Distributed Systems, Java, Spring Boot \| AI Infrastructure \| Ex\-Walmart, Amex

## About

I build backend systems that stay fast and stay up under real load\. At Walmart I cut pricing\-update latency by 45% on a platform serving 12M\+ users, and at American Express I kept fintech microservices running at 99\.98% uptime while meeting their compliance bar\. Most of my work is Java on the JVM: Spring Boot, Vert\.x, REST and event\-driven microservices, with Redis caching, real\-time stream processing on Apache Flink, and AWS underneath\. I have spent 10 years across fintech, retail, and content platforms, and most recently I have been at Turing building evaluation and training infrastructure for Google Gemini, where I apply the same backend discipline \(modular code, CI/CD, Docker\) to LLM pipelines\. I am looking for senior backend or platform engineering roles, fully remote, focused on distributed systems and large\-scale architecture\. Open to teams in the US, UK, and Europe\. Contact: bhawna\.faujdar@gmail\.com Skills: Java, Spring Boot, Vert\.x, Distributed Systems, Microservices, REST APIs, Event\-Driven Architecture, Apache Flink, Redis, AWS, Docker, Kubernetes, Apache Kafka, CI/CD, Jenkins, JUnit, Mockito, HBase, NoSQL, System Design

## Location

Greater Bengaluru Area

## Work experience

Lead Software Engineer \(AI Infrastructure\) at Turing, Mar 2025 \- Present · 1 yr 4 mos, Bangalore Urban, Leading a pod of engineers building evaluation and training infrastructure for Google Gemini LLMs, with a focus on reproducible pipelines, automation, and code quality\. Key contributions: \- Rebuilt LLM evaluation workflows as modular, containerized pipelines with CI/CD, which improved model accuracy and robustness by 23% and made test runs reproducible across versions\. \- Drive 23% improvement in model accuracy and robustness through Docker\-based reproducible testing environments\. \- Built automation around Git pull request workflows for multi\-version LLM compatibility testing \- saving the team 10\+ hours/week of manual effort\. \- Set the Java code\-review and system\-design standards for a pod of engineers building Gemini evaluation infrastructure, raising review throughput and cutting defects in shipped pipelines\. \- Partner with client stakeholders at Google to translate model performance requirements into engineering deliverables\.

Senior Java Developer \(AI\) at Turing, Feb 2025 \- Mar 2025 · 2 mos, Greater Bengaluru Area, Joined Turing's Google Gemini program as a backend engineer focused on LLM training and evaluation pipelines, applying 8\+ years of Java and distributed systems experience to AI infrastructure problems\. Key contributions: \- Trained and fine\-tuned Google Gemini LLMs using RLHF and RLEF techniques, improving model adaptability by 18% for high\-profile client use cases\. Optimized model alignment with human values by 22% through prompt engineering, benchmarking, and systematic evaluation\. \- Developed modular Java code for data processing and deployment pipelines, reducing development cycle time by 30%\. \- Built reproducible Docker\-based testing environments to ensure consistent model evaluation across versions\.

Senior Software Engineer, American Express \(Contract via Awign\) at American Express, Nov 2022 \- Feb 2025 · 2 yrs 4 mos, India, Full\-time remote contract engagement with American Express, delivering backend microservices for one of the world's largest financial services platforms\. Engaged through Awign Expert's enterprise engineering program\. Key contributions: \- Architected Vert\.x\-based microservices supporting enterprise\-scale fintech workloads, improving service performance by 35% while maintaining strict compliance requirements\. \- Designed and optimized REST APIs serving Amex's enterprise workloads, with Redis\-backed caching cutting API response times by 120ms at p99\. \- Tuned services for high\-availability fintech workloads, achieving 99\.98% uptime while meeting Amex's security and compliance standards\. \- Built and maintained Jenkins CI/CD pipelines with JUnit and Mockito test coverage, reducing deployment errors by 40% and enabling safer, more frequent releases\. \- Mentored junior engineers on Java best practices, microservice design patterns, and production readiness \- improving team delivery velocity by 25%\. \- Owned production support and incident response for fintech microservices, holding 99\.98% uptime across releases while coordinating with distributed Amex teams\.

Software Engineer\-III \(Walmart Mexico Team\) at WalmartLabs India, Aug 2018 \- Dec 2019 · 1 yr 5 mos, Bengaluru, Backend engineer on the Walmart Mexico platform team, building real\-time pricing and merchant\-facing systems serving 12M\+ users across Walmart's digital channels\. Key contributions: \- Architected and built a real\-time price update system enabling merchants to publish item attribute changes that reflect instantly across Desktop, mWeb, and native apps \- cutting update latency by 45% across all channels\. \- Designed the system to handle multiple overlapping pricing events and scheduled future changes, a critical capability for high\-volume retail campaigns and flash sales\. \- Developed backend services using Java, Spring Boot, and REST APIs, with Memcache\-backed caching to serve 12M\+ users at scale\. \- Built a Node\.js orchestration layer that aggregated downstream microservices behind an API proxy, accelerating delivery of new business requirements by 28% and standardizing authentication and security across the platform\. \- Collaborated across Bengaluru and Mexico City teams to ship features end\-to\-end \- from requirements to production \- in a large\-scale distributed engineering organization\.

Senior Software Engineer, Personalization, Data Platform at dailyhunt \(Versé Innovation Pvt Ltd\), Apr 2017 \- Jul 2018 · 1 yr 4 mos, Bengaluru, Backend and data platform engineer on Dailyhunt's Personalization team, building real\-time event processing and analytics infrastructure for one of India's largest news and content platforms\. Key contributions: \- Built Apache Flink jobs in Java to transform millions of user events per day into actionable insights for user\-level analytics, acquisition tracking, and engagement analysis \- improving analytics fidelity by 33%\. \- Automated HBase region balancing, eliminating manual ops toil and improving data distribution performance across the cluster by 40%\. \- Contributed to the data warehouse layer powering user personalization \- spanning Apache Flink \(stream processing\), HBase \(NoSQL storage\), Hive \(batch analytics\), and Kibana \(observability\) \- reducing downstream query latency by 200ms\. \- Operated distributed data pipelines in production: monitoring, tuning, and troubleshooting across multi\-node HBase and Flink clusters\. \- Followed CI/CD discipline with Git\-based workflows and automated build pipelines\.

Software Development Engineer 2 , Big Data \(AWS\) at Talentica Software, Mar 2015 \- Apr 2017 · 2 yrs 2 mos, Pune/Pimpri\-Chinchwad Area, Big data engineer on Talentica's analytics platform team, building and migrating large\-scale data processing pipelines on AWS EMR for enterprise analytics clients\. Key contributions: \- Wrote Java MapReduce jobs processing terabytes of data across distributed AWS EMR clusters \- improving data processing efficiency by 45%\. \- Migrated dedicated Spark infrastructure to AWS EMR Spark with spot instance optimization, cutting infrastructure costs by 60% and eliminating cluster maintenance and monitoring overhead\. \- Rewrote batch workloads using Spark's in\-memory computing model, reducing job execution time by 25 minutes per run and improving overall pipeline throughput by 50%\. \- Built comprehensive unit test coverage for MapReduce jobs using Mockito and MRUnit, enabling safe refactoring of data pipelines\. \- Followed CI/CD principles with Git\-based version control and automated build pipelines\.

## Education

Bachelor of Technology \(B\.Tech\.\), Computer Science, Vellore Institute of Technology

Central Board Of Secondary Education\(XII\), Sir Padampat Singhania School

[View the original profile](https://tal.club/meet/bhawna-3)

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