Vetted Engineering Professionals in the Bay Area

Anu Baluguri

Screened

Mid-Level Software Engineer specializing in cloud-native microservices and event-driven systems

San Francisco, CA4y exp

“Full-stack engineer with production experience at Atlassian and Zoho, spanning GraphQL federation, React/TypeScript frontends, and cloud-native AWS/Kubernetes operations. Built and operated a federated GraphQL gateway with Terraform + CI/CD + observability, delivering major latency and integration-time improvements, and also designed high-volume Kafka data pipelines (10M+ events/day) with strong reliability guarantees.”

Jason Shankel

Screened

Executive Software Engineer/CTO specializing in real-time 3D, game engines, and BIM platforms

San Francisco, CA28y exp

“Game/interactive systems engineer with shipped Unity/C# work (including performance gains on iOS) and experience building creator-facing tooling like a plain-language level scripting system. Also implemented an OpenAI-powered UGC dialogue/event generation pipeline with offline fallback, and built multiplayer collaborative editing in Unreal for an architectural drafting product using checksum + delta synchronization.”

Chitra Uppalapati

Screened

Entry-level Software Engineer specializing in full-stack and machine learning applications

Sunnyvale, CA1y exp

“Built production Python data integrations and dashboard automation for incident analytics, with a strong focus on data quality, observability, and reliability for leadership-facing reporting. Also translated an ambiguous manual creator evaluation process at startup Spring into an automated predictive scoring feature, showing a blend of backend data engineering, test automation, and cross-functional product thinking.”

“Data/pipeline engineer with experience in space and scientific data systems, including JPL-related satellite transmission workflows and customer deployments involving NOAA/Argo standards. Stands out for building autonomous production pipelines, debugging subtle logic failures in data integrations, and improving processing efficiency while reducing manual operational work.”

Arjun Kulkarni

Screened

Junior Software Engineer specializing in AI, LLM systems, and healthcare applications

San Francisco, CA3y exp

“Product-minded full-stack engineer with experience improving performance, UX, and platform architecture across startups including SideShift, Curator, Congruence, and work on an AI coding assistant called Exec. Stands out for cutting messaging-system Redis traffic by roughly 95%, redesigning user flows for faster adoption, and building reusable multi-tenant systems and cross-platform APIs without over-abstracting.”

“Full-stack engineer who built and owned a production real-estate search platform (advanced search + saved-search alerts) using Next.js App Router/TypeScript with a NestJS + Postgres + Elasticsearch/Kafka backend. Demonstrated strong performance engineering (map search FPS ~20→60, ~80% latency reduction) and backend scalability (optimized alert-matching queries and orchestrated notification workflows with Airflow/Redis), with measurable post-launch engagement gains (+27% returning users).”

“Robotics software engineer at Tesla who led end-to-end development of a distributed real-time control and orchestration platform for autonomous systems. Deep production ROS 2 experience (nav2, slam_toolbox), with demonstrated wins reducing end-to-end latency 25–30%+ via profiling, multithreaded executors, and QoS tuning, plus simulation and deployment at scale using Gazebo/Webots, Docker/Kubernetes, and CI/CD.”

“Built a production LLM-powered analyst assistant at Discern Security to speed up SOC investigations using a RAG pipeline over security vendor documentation (Python PDF ingestion, vector search). Demonstrates deep, security-critical LLM engineering: structure-aware chunking with custom table parsing, grounded/cited responses, prompt-injection defenses, and post-generation validation, validated via golden datasets and adversarial testing; tool is used daily by analysts.”

“Software engineer with experience at PayPal and JPMC building large-scale onboarding/account setup systems using React/TypeScript with Spring Boot/Node microservices and Kafka. Also built an Ignition-based SCADA monitoring tool at Mainspring Energy that became the default for manufacturing/test engineers by aggregating real-time telemetry and historical test data.”

Amit Sharma

Screened

Principal Software Engineer specializing in AI/LLM platforms, payments, and healthcare systems

San Francisco, CA25y exp

“Engineering player-coach who recently shipped an agent-based workflow to extract key info from unstructured web data (browser agents + CDP) and populate daily digests/calendars, owning architecture through testing. Also built a Flask-based LLM evaluation and regression testing system using G-Eval/Confident AI dashboards, and applies a rigorous, research-driven approach to selecting third-party tools with stakeholder buy-in; has healthcare ops/onboarding workflow experience at Vivio Health.”

Sahil Kakadiya

Screened

Junior Embedded Systems & Wireless Software Engineer specializing in BLE/Wi-Fi performance

Mountain View, CA2y exp

“Master’s capstone contributor on an autonomous rover navigation project, serving as an embedded/robotics software designer. Built low-level wheel control and odometry from encoders, integrated RealSense and RPLidar via ROS, and solved sensor-fusion/coordinate-frame issues by creating custom TF transforms. Used Gazebo to debug sim-to-real behavior and improved reliability on rough terrain by moving to dual-channel encoders when IMU data proved unreliable.”

Alex Vo

Screened

Staff Backend Software Engineer specializing in telemetry pipelines and observability

San Jose, CA3y exp

“Backend engineer from VMware focused on proprietary enterprise systems (monitoring tools, data pipelines, and APIs). Drove a ClickHouse migration POC (local to remote host) using a dual-write/cutover approach and source-level debugging across Node/driver differences during a Node 12→20 upgrade, and delivered measurable performance gains (~20% CPU/memory improvement) through batching and streaming ingestion.”

Sanjay Santhanam

Screened

Mid-level AI Software Engineer specializing in LLMs and FinTech data systems

San Jose, CA4y exp

“Backend/AI systems engineer focused on productionizing agentic document-processing workflows for large financial PDFs. They describe owning deployments end-to-end, combining Python, Redis, LLM function calling, RAG/ReAct-style orchestration, and strong reliability practices to deliver 80% faster processing, reduce parsing errors from 12% to ~1%, and sustain 99.9% uptime in high-concurrency environments.”

“Product-focused full-stack engineer building a GenAI-powered case summarization workflow for a telemetry dashboard, spanning React/TypeScript UI (confidence indicators, reasoning traces) and Python/FastAPI backend with caching to control LLM latency/cost. Has operated services on AWS (ECS Fargate, RDS Postgres, S3) and Kubernetes, and has hands-on experience resolving real production latency incidents through query/index optimization and caching.”

“QA professional with ~7 years of experience working in Scrum teams, involved from requirements and user story creation through test strategy/planning, execution, defect triage in Jira, and verification. Highlighted catching multiple issues early on an AI-driven project to avoid production regressions and escalating a blocker where a frequently used UI was broken to get it fixed quickly. Has not shipped an AAA game title.”

Alex ZhuZhou

Screened

Intern Full-Stack Software Engineer specializing in AI/LLM platforms and data systems

Berkeley, CA2y exp

“Backend/LLM engineer with experience productionizing RAG systems (legal-case natural language querying) and optimizing for latency/cost, including a reported ~40% reduction via Redis caching and batching. Built monitoring and real-time debugging workflows (FastAPI, structured logging, correlation IDs, sandbox repro) and regularly delivered technical demos/workshops. Also partners with BD/sales to translate LLM capabilities into business value, including ESG-metric extraction from corporate filings.”

Bhargava Prabu Reddy Mallikarjuna

Screened

Mid-Level Full-Stack Software Engineer specializing in automation, microservices, and cloud deployments

Cupertino, CA3y exp

“Full-stack engineer with experience at Apple, Walmart, and a healthcare startup (Legacy), building customer-facing PWAs and internal platforms. Delivered HIPAA-compliant clinician/patient workflows with rapid weekly releases and measurable engagement gains, and built scalable automation/testing and real-time analytics systems using Next.js/React/TypeScript, Node/FastAPI, Redis, and PostgreSQL.”

Lamar Petty

Screened

Mid-level Full-Stack Product Engineer specializing in data-driven web apps and healthcare systems

San Francisco, CA13y exp

“Full-stack engineer with production experience shipping a healthcare-focused web app (Pregnancy-Pal) using Next.js/TypeScript on GCP, integrating a Python/Flask middleware and FHIR server for patient/practitioner dashboards and messaging. Former Wikimedia Foundation Android engineer who led the end-to-end 'Year in Review' feature and built robust automated testing/CI practices (Espresso, GitHub Actions matrix). Strong emphasis on reliability via rigorous validation, comprehensive Postman testing, and detailed API documentation.”

“End-to-end deployment owner for Oracle document delivery/print services in a hospital-like production environment, focused on reliability/performance at scale (thousands of systems). Also describes implementing event-driven RAG/agentic LLM workflows with attention to embeddings/index consistency, latency, and measurable improvements in response relevance and operational efficiency.”

“Built Baioniq, an enterprise LLM platform for automating extraction from massive unstructured documents like contracts and insurance claims. They demonstrate unusually strong production depth in agentic AI—scaling to 100k+ requests/day, processing 1M+ claim documents, and improving extraction accuracy through rigorous RAG architecture, evaluation, and fallback design.”

Joseph Villanueva

Screened

Senior Software Engineer specializing in full-stack SaaS and Healthcare IT

San Francisco, CA8y exp

“Product-minded software engineer from Gusto who has shipped internal AI agent capabilities and end-to-end user-facing features across frontend and backend. Stands out for making pragmatic architecture tradeoffs—moving from OpenAI prototypes to deterministic systems when accuracy, latency, and uptime mattered—while still improving LLM workflow quality and reducing tool-calling errors by 15%.”

“Frontend/product engineer from IXL who built an AI workspace for teachers to generate, edit, and chain classroom resources using LLMs. They show unusual depth in browser fundamentals and rich-text/math UI work, including debugging a rare repaint issue and designing mixed text/LaTeX editing experiences for educators.”

Eric Lee

Screened

Mid-level Software Engineer specializing in full-stack and AI-powered systems

San Jose, CA3y exp

“Software engineer with experience spanning startup-style full-stack product work and large-scale Amazon backend systems. Built and owned an AI-powered recruiting workflow in Next.js/TypeScript/Prisma/PostgreSQL, and previously improved Alexa service scalability at Amazon by driving a caching change that cut API traffic by about 30%.”

“Backend-focused Python engineer who built an end-to-end personalized chatbot service integrating Amazon Redshift context retrieval with Amazon Bedrock, including prompt construction and production-grade reliability controls. Strong platform experience deploying containerized services to Kubernetes with GitOps/ArgoCD, plus hands-on Kafka streaming and phased infrastructure migration execution.”