# Vamshi Krishna Kyatham > I do what AI can’t. Location: Sunnyvale, California, United States Profile: https://flows.cv/vamshikrishnakyatham With 3 years of experience, I specialize in designing and developing scalable, high-performance, and distributed software products across the full stack. My expertise spans backend, frontend, data engineering, and cloud infrastructure, ensuring robust and efficient solutions. Tech Stack: ✅ Backend: Spring Boot, Node.js, Next.js, Flask ✅ Frontend: React, Next.js ✅ Data & Streaming: Apache Kafka, Spark, Flink, Redis, RabbitMQ, Akka, Hazelcast ✅ Databases: SQL, PostgreSQL, MySQL, MongoDB, DynamoDB, InfluxDB, Cassandra, ElasticSearch, Firebase ✅ Cloud & DevOps: AWS, Google Cloud, Docker, Kubernetes, Jenkins, ArgoCD, Terraform, Tekton, Helm Charts ✅ Monitoring & Observability: Grafana, Prometheus ✅ Testing: JUnit, Mockito, Selenium, TestNG I always follow System Design Patterns when I code. Beyond software engineering, I am a competitive programmer, consistently solving complex algorithmic challenges. LeetCode Top 1% (Guardian), Expert at Codeforces, 4★ CodeChef. 📌 Competitive Programming Profile: [https://clist.by/coder/vamshikrishnakyatham] Always open to opportunities where I can build cutting-edge, optimized, large-scale distributed software products. 🚀 ## Work Experience ### Software Engineer @ Onehouse Jan 2025 – Present | Sunnyvale, California, United States Open Source Contributor - Apache Hudi (Open Data lakehouse) Core Contributor - Optimizations related to Apache Spark, Query Execution and overall Onehouse Product. ### Graduate Teaching Assistant @ University at Buffalo Jan 2025 – Jan 2025 | Buffalo, New York, United States My responsibilities include: • Providing academic support to a cohort of 150+ students in CSE 4/560 - Data Models and Query Language, clarifying doubts and enhancing their understanding of Relational Algebra, SQL, ER Models, Normalization, Indexing, Transactions, Hashing, Locking, Concurrency Control, and Recovery Algorithms. • Assisting in designing and grading project, assignments focused on database design, query optimization, and transaction management, ensuring students grasp core database concepts and real-world applications. • Developing and distributing lecture materials, project handouts, and SQL practice problems to reinforce learning. • Managing exam logistics, proctoring, and maintaining student performance records. • Collaborating with the instructor to update course content, create new problem sets, and enhance coursework to align with industry standards. ### Teaching Assistant @ University at Buffalo Jan 2024 – Jan 2025 | Buffalo, New York, United States My responsibilities include: • Provide academic support to a cohort of 250+ students in the CSE 4/587 - Data Intensive Computing course, helping to clarify doubts and enhance understanding of complex topics including Machine Learning, Data Science Life Cycle, Hadoop, HDFS, Spark, and Spark Streaming. • Grade projects, homework, and assignments, delivering timely and constructive feedback to foster student improvement. • Assist in preparing and distributing course materials, such as lecture notes and project handouts, ensuring alignment with course objectives. • Maintain accurate records of student grades and manage logistics for exams, including scheduling and proctoring to ensure smooth course operations. • Support the instructor in developing, updating, and refining course content, assignments, and projects, contributing to the planning and execution of course activities to enhance the learning experience. ### Research Assistant @ University at Buffalo Jan 2024 – Jan 2025 | Buffalo, New York, United States Researcher and Full Stack Engineer at Data Intensive Distributed Computing Lab contributing to One Data Share project. Devised core services for OneDataShare, including a Single Sign-On feature for social and organizational logins using OAuth2 and OIDC Security Protocols. Optimized cross-platform data transfer through Bayesian Optimization, DDPG, and PPO by 90% predicting optimized transfer parameters. Worked on reducing carbon footprint for AI models with architectural improvements and split machine training with efficient routing for back propagation. ### Data Annotator @ The Research Foundation for SUNY Jan 2024 – Jan 2024 | Buffalo, New York, United States Performed detailed geographical location and address annotations ensuring data integrity and accuracy across large postal databases. ### Software Engineer @ Finta Jan 2024 – Jan 2024 | New York, United States • Contributed to architecting Aurora, a Fundraising Copilot leveraging an advanced RAG pipeline with LangGraph, implementing multi-stage retrieval optimization with hybrid search techniques and custom-trained language models to provide better responses and highly relevant investor recommendations. More at: https://www.trustfinta.com/blog/finta-product-update-introducing-investor-intelligence • Designed and implemented large-scale ETL pipelines for Aurora, a Fundraising Copilot, leveraging Apache Flink, Spark, and LangGraph to optimize multi-stage retrieval with hybrid search techniques and LLM-powered data processing. • Engineered an AI-powered Investor Network Recommendation Engine that analyzes email interactions and web-scraped investor data to calculate relationship strength and investment probability. Implemented intelligent matching algorithms, reducing investor search time by 65%. More at: https://www.trustfinta.com/blog/finta-networks-sync-and-share-connections • Leveraged LLM-powered tools like APIChain, RequestsTool, and PythonREPLTool for dynamic web scraping, structured data extraction, and real-time information retrieval to refine investor intelligence. • Built high-performance data pipelines using Apache Kafka, Spark Structured Streaming, and Flink for real-time data ingestion, transformation, and AI-driven analytics. • Engineered scalable data infrastructure, integrating Google BigQuery, Snowflake, and Elasticsearch, improving data indexing, search efficiency, and retrieval speed by 40%. • Automated ETL workflows with Airflow and dbt, optimizing data transformation, orchestration, and lineage tracking for investor insights and business intelligence. • Managed end-to-end data lifecycle, deploying solutions on Google Cloud Run, Kubernetes, and Terraform, ensuring high availability, scalability, and resilience ### Software Development Engineer @ Phenom Jan 2022 – Jan 2023 | Hyderabad, Telangana, India • Architected and Engineered Flow Designer and Connector Builder, an alternative to Flow Studio at Phenom, a low/no-code platform with drag-and-drop connectors for high-level flow and sub-flow creation. This tool automates the implementation of process functions for the Extraction, Transformation, and Load (ETL) phases, including Fetching, Splitting, Extracting, and Evaluating from ATS by autogenerating Flink code, Manifest files, and Dockerfile build using Apache Velocity, Apache Ant and ANTLR. Additionally, designed and built a JAR Server to automate JAR file creation for the autogenerated code, which is then used to generate a Docker image that is seamlessly pushed to AWS S3. Automated the deployment of the autogenerated application using Terraform and Tekton, orchestrating CI/CD pipelines to seamlessly deploy applications to Kubernetes (K8S). It internally implements Flink test cases and also conducts comprehensive integration testing during the CI/CD to ensure the reliability and performance of the autogenerated Flink Spring Boot application. • Developed an on-demand data migration system using Apache Flink and Apache NiFi for extracting candidates from open jobs and user-specified jobs in Workday ATS, achieving an 88% optimization in the extraction phase. Leveraged Apache NiFi for transformation and load phases, integrating with the Flink backend via Kafka events to handle real-time data streaming. Utilized big data techniques to optimize performance and scalability. Managed both backend development and deployment operations. • Designed fault-tolerant and scalable streaming workflows to handle large volumes of recruitment data while maintaining data consistency and low-latency processing. • Worked on fetching the delta candidates for SuccessFactors ATS using Apache Flink Spring Boot application and Apache NiFi. • Integrated video assessment workflows into the recruitment pipeline, enabling automated candidate evaluations through self-video assessments. ### Software Engineer @ Brane Enterprises Pvt Ltd Jan 2021 – Jan 2022 | Hyderabad, Telangana, India • Played a crucial role in engineering scalable Spring Boot backend services for survey collection and seamless payment integration, ensuring high availability, security, and optimized performance. • Built real-time Grafana dashboards to monitor metrics, and performance, enhancing decision-making efficiency and insights. • Enhanced operational efficiency by implementing multi-threading and caching solutions using Redis. • Enhanced data streaming algorithms using Dynamic Programming (DBSCAN algorithm) which updates clusters dynamically without recomputation achieving a reduction of time complexity by 50%. ## Education ### Master of Science - MS in Computer Science and Engineering University at Buffalo ### BE - Bachelor of Engineering in Computer Engineering Osmania University ## Contact & Social - LinkedIn: https://linkedin.com/in/kyatham-vamshi-krishna-990b13175 - Portfolio: https://vamshikrishnakyatham.github.io/personal-portfolio/ - Portfolio: https://clist.by/coder/vamshikrishnakyatham/ --- Source: https://flows.cv/vamshikrishnakyatham JSON Resume: https://flows.cv/vamshikrishnakyatham/resume.json Last updated: 2026-04-10