Amit Chavda

Cloud-native Java Backend Engineer with 6+ years architecting high-scale microservices for Mercedes-Benz (10M+ connected vehicles) and Enphase Energy (global solar monetization platform). Delivered zero-defect Spring Boot 2-to-3 migration across 5+ years of legacy code. Drove 27-30% performance improvements through caching redesigns and code optimization.

Proven track record owning production reliability for mission-critical automotive and energy systems across US, EU, and India. Leveraging AI-powered tooling and automation workflows to accelerate incident diagnosis and developer productivity.

Lead Developer - Java Backend at IBM (Client: Mercedes-Benz Research & Development India - MBRDI) (2024-08 – Present)

Tech Stack: Java 17/21, Spring Boot 3.x, Maven, Azure AKS, Kafka, Redis, Datadog, Gitlab CI/CD, Terraform, Claude, N8N

• Engineered remote vehicle control commands (engine start/stop, charge scheduling, onboard/offboard geofencing) for a platform serving 10M+ Mercedes-Benz connected vehicles globally
• Redesigned geofencing API layer with Redis caching and refactored legacy business logic, reducing p95 latency by 30% and eliminating timeout-related production escalations
• Spearheaded Spring Boot 2-to-3 migration of a critical microservice - resolved 40+ outdated dependencies, patched security vulnerabilities, and aligned all libraries with Spring Cloud BOM; 0 defects in production for 6+ months
• Collaborated with cross-functional teams in Germany during production validation sessions and WAR-room exercises with live Mercedes-Benz vehicles
• Owned production incident lifecycle: triage via OpsGenie/Datadog alerts, root cause analysis, remediation, and stakeholder escalation for infrastructure changes (pod scaling, CPU allocation)
• Competed in MBRDI internal hackathons; winning idea recognized by senior leadership for optimizing the deployment pipeline of the platform's most critical service (100+ commands routed)
• Built an internal test-environment orchestration platform from scratch (Python, React), revolutionizing the testing workflow for ~10 cross-functional teams across MBRDI
• Delivered the full platform in 2 months with complete end-to-end ownership - architecture, backend, frontend, and deployment- compressing what was estimated as a 6-to-10-month effort
• Enabled teams to provision, configure, and manage isolated test environments on-demand, significantly reducing inter-team blocking and accelerating release cycles
• Leveraged Claude (via Azure MCP) and N8N to build an AI-powered incident response pipeline: natural-language KQL querying, automated RCA drafting, and RAG-based retrieval of historical resolutions from internal runbooks - reducing mean-time-to-diagnose for on-call engineers
• Developed custom Claude skills for coding standards enforcement, boilerplate generation, and context-aware code review
• Integrated LLM-based test case generation into legacy code workflows, producing JUnit scaffolds from method signatures to accelerate coverage during Spring Boot migration

Senior Software Engineer at EInfochips (An Arrow Company) (Client: Enphase Solar Energy Pvt. Ltd.) (2021-01 – 2024-08)

Tech Stack: Java 8/17, Spring Boot 2.x/3.x, Gradle, AWS, Kafka, Redis, Datadog, Bitbucket, Jenkins

• Owned end-to-end delivery of 5 microservices powering global electricity tariff optimization (Dynamic Pricing, NEM 3.0) across US, EU, and UK markets
• Architected tariff intelligence engine enabling homeowners to monetize stored solar/grid energy based on real-time pricing signals
• Delivered interactive consumption dashboards showing daily usage, solar generation, and battery reliance with pre-optimized savings profiles
• Boosted system performance by 27% through targeted version upgrades, query optimization, and dead-code elimination
• Enforced 92% coverage floor via JUnit parameterized test standards and mandatory peer review gates
• Integrated third-party home appliances (Washing Machines, Dryers, Dishwashers) into the main application
• Implemented OAuth to link user BOSCH accounts, capturing appliance events and sending them to Kafka to extract session histories
• Recommended optimal appliance operation schedules to minimize user costs based on low tariff rates and home electricity consumption - launched beta in Germany with near-zero defect rate

B. Tech. in Information Technology – Institute of Technology, Nirma University (2017 – 2020)