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