Software Engineer - AI Systems & Web Apps Specialist

Sanjeev Vijayakumar

New York, USA ******@***.*** +1-585-***-****

github.com/sanjeevmax6 linkedin.com/in/sanjeev06/ sanjeevmax6.github.io/ WORK EXPERIENCE

Nokia Sunnyvale, CA

Software Engineering Intern September 2025 – Present

● Architected an Agentic AI system using LangChain & MCP client/server architecture, producing a multi-node pipeline to fetch, reason over, and generate network testbed config files.

● Designed the Orchestration layer using PostgreSQL (JSONB, pgvector) indexing over 5000+ JSON files, and an Airflow based parallelized batch ingestion pipeline for human-in-the-loop reasoning.

● Engineered a TypeScript powered agent workspace with session memory and schema-driven editing, thereby reducing a manual workflow from 4 h to 10 min.

● Technologies: LangGraph, MCP Servers, Agentic AI, Vector Retrieval, PostgreSQL, React, TypeScript, Airflow Skillz Las Vegas, NV

Software Engineering Intern August 2024 – January 2025

● Built the MVP Phase Web SDK using React, TypeScript, and Next.js, implementing reusable UI components and integration hooks consumed across 500+ games and 1000+ DAU.

● Shipped 20 cross platform features via OTA updates, building the Daily Challenges modal (7-day rewards system) using the skillz-ui component library and React Query optimized state management.

● Resolved 10+ critical bugs weekly across Store and Rewards flows, including deep-link failures, cash discrepancies between mobile/web, and Datadog exceptions, by writing unit tests & giving active code reviews.

● Technologies: React, React Native, JavaScript, TypeScript, Java, NextJS, Jest, Git, Jenkins Spider R&D Tiruchirappalli, India

Senior Application Developer September 2020 – May 2022

● Led development of production-grade, customer-facing applications with over 800 users, by applying object-oriented design principles (OOP), and designing modular architectures using React Native, Node.js, and Firebase.

● Architected an Orientation app using Flutter, MongoDB, integrating Google Maps & cloud-hosted, NoSQL backend.

● Spearheaded full-cycle recruitment, conducted interviews, & mentored juniors, thereby promoting best practices in coding.

● Technologies: React Native, Flutter, Android Native, JavaScript, Node.js, Firebase, MongoDB PROJECTS

Live Captioned Meeting App (Accessibility) [Node.js, WebSockets, React, Google ASR, Signal-to-noise] [Code]

● Built an accessibility enabled meeting app using Node.js, WebSockets, React, & Google’s ASR engine for live captions.

● Designed an ASR evaluation pipeline that systematically varies signal-to-noise ratio via white-noise injection, measuring WER (Word Error Rate) impact on live caption output. Brevity Cloud – AI Webpage Summarizer [AWS, S3, DynamoDB, Kendra, Amplify, Terraform, Docker] [Code]

● Built and deployed a serverless chrome extension using AWS Bedrock and Kendra for real-time, in-browser, context- aware data, handling 100s of concurrent requests (<200ms) via Docker (ECS), Lambda, and IAM-secured API Gateway.

● Designed fault-tolerant infrastructure with Terraform-provisioned VPCs and S3 + DynamoDB for reliable document ingestion, retrieval, and secure access control.

Real-time CI/CD Test Case Prioritization [Python, Travis CI, Reinforcement Learning, Dash] [Code]

● Developed a reinforcement learning-based test case prioritization framework to intelligently reorder failing tests, thereby reducing CI pipeline latency by 50% and improving early fault detection.

● Built a real-time dashboard using Plotly Dash to visualize the agent’s incremental learning, driven by CI build logs, scraped using Travis CI from popular open-sourced repositories like Kubernetes & OpenXLA. Stock Market Microstructure Backtest & Cost Modeling [Python, NumPy, Kafka, Terraform, Backtesting] [Code]

● Modeled a trading platform to distribute money orders across 600 trading venues, using a min greedy cost strategy with parallel processing, cache-optimized data flows, and auto-deployment on AWS EC2 via Terraform.

● Designed real-time Kafka streaming, to simulate step-by-step buying with observability for cost & fill efficiency. TECHNICAL SKILLS

Languages: TypeScript, Python, SQL, Shell Scripting (Bash), C++, Java DB: PostgreSQL, MongoDB, Neo4j, Redis Frontend: React (Web/Native), Next.js, Flutter, Vite, Tailwind CSS Backend: Node.js, Go, GraphQL, WebSockets Cloud: AWS, Terraform, Kubernetes, Docker, Firebase, Airflow, Kafka AI / ML: PyTorch, Transformers, RAG, LangGraph EDUCATION

Rochester Institute of Technology – Master of Science May 2026 Courses: Large Language Models (LLM) RAG Front End Engineering Cloud Engineering Reinforcement Learning National Institute of Technology Tiruchirappalli – Bachelor of Technology May 2023 Courses: Low Level Programming Database Management Systems Operating Systems Data Structures & Algorithms

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