Headline

Software Engineer @ ChargePoint | Java · Spring Boot · Kafka · Distributed Systems · Microservices | MS CS, ASU (4.0 GPA) | NAACL ’24

About

Software Engineer at ChargePoint building the backend infrastructure that powers EV charging at scale. I design event-driven microservices, Kafka-based messaging pipelines, and fault-tolerant distributed systems in Java and Spring Boot. What I've shipped recently: → Led a zero-downtime migration of 10,000+ cloud licenses across platforms, owning the full system design from HLD through production deployment → Built a Kafka priority coordinator with weighted consumer groups that improved message throughput by 3x → Designed a notification microservice decoupling 4 legacy communication flows into an independently deployable service → Instrumented production services with Prometheus, Grafana, and Splunk — reducing incident detection time from 15 min to under 3 min Previously built backend systems at ChargeMate.ai (Spring Batch pipelines, vector search with Pinecone) and W4M.AI (Python/FastAPI microservices, RAG pipelines with LlamaIndex). Published researcher with papers at NAACL '24 and EACL '23 on instruction-tuned NLP models and LLM reasoning benchmarks. M.S. Computer Science, Arizona State University (4.0/4.0 GPA) B.Tech Computer Science, SRM Institute of Science & Technology (8.7/10) Tech: Java, Spring Boot, Python, Apache Kafka, Microservices, REST APIs, PostgreSQL, MongoDB, Redis, Docker, Kubernetes, AWS, Grafana, Prometheus, Datadog

Location

Bengaluru

AI stack

claude code

claude

codex

cursor

deepmind

gemini

Work experience

Software Engineer at ChargePoint, May 2025 - Present · 1 yr 7 mos, Bengaluru, Karnataka, India, Building backend infrastructure for ChargePoint's cloud platform — designing event-driven microservices, Kafka pipelines, and distributed systems in Java/Spring Boot. Key contributions: • Led a cloud-license migration from legacy NOS to the SUITE platform, owning full HLD/LLD design, ETL pipeline, and migration of 10,000+ licenses with zero data loss • Built a Kafka-based two-way sync keeping NOS and SUITE consistent in real time through a one-month cutover until 100% of traffic shifted • Designed an event-driven notification microservice with REST APIs, deferred queuing, and quota management — decoupling 4 legacy communication flows • Built a Kafka priority coordinator with multi-threaded, weighted consumer groups, improving throughput by 3x • Instrumented services with Prometheus + Grafana/Splunk dashboards, reducing MTTD from 15 min to under 3 min • Mentored 2 engineers, authored design docs/runbooks, cut new-engineer setup time by 40% Tech: Java, Spring Boot, Apache Kafka, PostgreSQL, REST APIs, Prometheus, Grafana, Splunk, Docker, Kubernetes

Software Engineer at ChargeMate, Jul 2024 - Jan 2025 · 7 mos, San Francisco Bay Area, Built backend systems powering an AI-driven EV diagnostics platform using Java/Spring Boot. • Developed production REST APIs with multi-threaded processing and comprehensive JUnit/Mockito test suites, improving diagnostic troubleshooting efficiency by 30% • Built a Spring Batch pipeline for automated query classification/routing, integrated Pinecone Vector DB (10K+ embeddings) for semantic search — reducing chatbot escalation by 15% • Owned the deployment pipeline with Docker, environment configs, and automated regression — weekly releases with zero rollbacks Tech: Java, Spring Boot, Spring Batch, Pinecone, JUnit, Mockito, Docker, REST APIs

Software Engineer - ML at W4M.AI, Feb 2024 - Jul 2024 · 6 mos, San Francisco Bay Area, Built Python/FastAPI microservices and ML pipelines for an AI search platform. • Developed microservices with ML-powered data pipelines serving 5K+ daily requests, maintained CI/CD (Jenkins, GitHub Actions) with 90%+ code coverage • Integrated Datadog for distributed tracing, reducing P99 latency debugging time by 50% via correlated trace-to-log analysis across 6 microservices • Implemented RAG pipelines using Mixtral and LlamaIndex for AI search services with Llama-3 language models Tech: Python, FastAPI, Datadog, Jenkins, GitHub Actions, LlamaIndex, Mixtral, Llama-3

Internship Trainee at Indian Institute of Technology, Kanpur, May 2019 - Aug 2019 · 4 mos, Kanpur, Uttar Pradesh, India, Spearheaded the development of an autonomous road sign detection system, based on YOLO-v3. Was involved in data preprocessing and training the CNN model with our custom data. Successfully deployed the model on Raspberry Pi, demonstrating strong technical and project management skills.

Education

Masters of Science, Computer Science, Arizona State University

Bachelor of Technology, Computer Science Engineering, SRM IST Chennai

Public links

github: https://github.com/siddharth2011

leetcode: https://leetcode.com/siddharthgoyal198