About Me

Hi, I’m Sreekar — a Vice President and Senior Software Engineer at Goldman Sachs in Salt Lake City, UT. I build event-driven platforms and distributed systems with 7+ years of experience across Java, Kafka, Kubernetes, AWS, and observability. I lead the Client Communication Platform for Private Wealth Management, delivering 150+ global communications at ~93% e-delivery to tens of thousands of clients, processing 100K–1M Kafka events daily across 10+ microservices.

Experience

Vice President, Senior Software Engineer
Goldman Sachs · Salt Lake City, UT
Mar 2022 – Present

• Lead engineer for the Client Communication Platform supporting Private Wealth Management, delivering 150+ global communications with ~93% e-delivery adoption across tens of thousands of clients.
• Led migration of the platform to an event-driven architecture (Kafka + MongoDB), authoring event schemas and orchestration flows across 10+ microservices that now process 100K–1M events daily.
• Contributed to building an AI-powered code review agent integrated into CI/CD pipelines — adopted across four teams in the division — to automate merge-request analysis, enforce code quality standards, and surface defect detection and fix suggestions.
• Strengthened platform security by implementing Spring Security, JWT, and OAuth2 across the platform’s internal admin and client-facing application layers, standardizing token handling across services.
• Designed and launched a custom MongoDB-to-Prometheus metrics exporter adopted across the division (4 teams), enabling proactive alerting and helping prevent potential SLA breaches.
• Established a standardized observability platform on OpenShift/Kubernetes using Prometheus, Grafana, Elasticsearch, Jaeger, and OpenTelemetry with Helm-based infrastructure automation, significantly improving production visibility and debugging efficiency.
• Automated post-deployment regression testing through CI/CD pipeline integrations across repositories, reducing manual release validation effort and accelerating deployments.
• Contributed to blue-green and canary deployment capabilities that improved release safety and enabled zero-downtime production changes.
• Lead backend development for the Documents module on the goldman.com PWM portal, building an aggregation service that fetches, consolidates, and serves client documents at scale to tens of thousands of users.
• Lead AWS cloud migration strategy for the platform, delivering an initial ECS/Fargate pilot and establishing reusable patterns for broader cloud adoption.
• Mentored engineers across the team on system design, code quality, and platform best practices.

ML Cloud Tools Developer Intern
Siemens Healthineers · Malvern, PA
May 2021 – Nov 2021

• Built a Python DICOM medical image viewer using memory-mapped processing, achieving 10× memory efficiency on large radiology datasets.
• Developed a React-based UI that improved medical image rendering and viewer performance for clinical workflows.

Graduate Research & Teaching Assistant
UNC Charlotte · Charlotte, NC
Sep 2020 – May 2021

• Developed NLP models extracting causal relationships from S&P 500 financial reports (78% model accuracy); research subsequently published in MDPI Information journal (2023).
• Teaching Assistant for Database Systems, supporting graduate and PhD students through recitations and course material development.

Systems Engineer
Tata Consultancy Services · Hyderabad, India · Client: Citigroup
Jun 2016 – Oct 2019

• Designed and delivered multiple Spring Boot microservices for Citigroup, including a centralized Spring Batch monitor; achieved 95% unit test coverage using JUnit and Mockito.
• Performed data extraction, cleaning, and exploratory analysis for regression and clustering models using AbInitio across SQL Server, Excel, flat-file, and JSON sources.
• Wrote complex optimized SQL queries to extract and aggregate large volumes of data; added indexes to legacy SQL modules, improving query response time by 40%.

Skill Set

Languages: Java, Python, JavaScript, SQL
Distributed Systems: Apache Kafka, Microservices, Event-Driven Architecture
Frameworks: Spring Boot, Spring Batch, Node.js, React, gRPC
Databases: MongoDB, MySQL, SQL Server
Infrastructure: Kubernetes, OpenShift, Docker, Helm, Terraform, ArgoCD, AWS ECS (Fargate)
Observability: Prometheus, Grafana, Elasticsearch, Log4j2, OpenTelemetry, Jaeger, Alertmanager
API & Security: REST APIs, Kong API Gateway, OAuth2, JWT, Spring Security
Data & ML: Pandas, NumPy, scikit-learn, NLP, BERT, HuggingFace Transformers
AI Productivity: GitHub Copilot, Claude Code, AI-augmented code review tooling
CI/CD & Practices: CI/CD Pipelines, Agile/Scrum, DORA Metrics, OOP, TDD, Blue-Green & Canary Deployments

Education

M.S. in Computer Science — GPA 4.0/4.0
University of North Carolina at Charlotte · Dec 2021
Coursework: Algorithms · Machine Learning · Big Data · Cloud Data Storage · Database Systems · Computer Networks · Intelligent Systems

B.Tech in Electronics and Communication Engineering
CVR College of Engineering · Jun 2016

Publications & Awards

Publications

• “Text to Causal Knowledge Graph” — NSF-funded BERT-based NLP pipeline achieving F1-score of 89%. Published in MDPI Information journal, Vol. 14(7), June 2023. DOI: 10.3390/info14070367

• “ASIC Implementation of Three Stage Data Path Logic Structure” — Published in International Journal of Innovative Research in Science, Engineering and Technology (IJIRSET), Impact Factor 5.442.

Honors

• Member, Phi Kappa Phi Honor Society — top 7.5% of graduate class.
• Received Service and Commitment Award from Tata Consultancy Services.
• First prize in technical paper presentation on “NFC” at state-level symposium Srujana 2K15, JNT University, Hyderabad.

Projects

Real-Time Credit Card Fraud Detection
• Implemented a Big Data pipeline using Apache Spark Streaming integrated with Kafka and Cassandra.
• Built a Random Forest classification model with K-means data balancing, detecting unusual spending based on prior habits.
• Achieved exactly-once semantics using Spark Streaming custom offset management; automated Spark jobs via Airflow on a Spark Standalone Cluster.

Movie Recommender System
• Addressed the "cold start" problem using Wikipedia as a metadata source, clustering with K-means and enriching with IMDB ratings to form a content-based recommendation system.
• Code available on GitLab.

ShopAnything — E-Commerce Platform
• Built a full-stack e-commerce application using Java Spring MVC, Spring Data, Hibernate, JPA, and Spring Security.
• Implemented a secure admin portal for inventory management and a customer-facing cart and checkout flow.
• Source code on GitHub.

My Motto: “The only way to do great work is to love what you do.”