Vetted Performance Optimization Professionals

Peeyush Dyavarashetty

Screened ReferencesModerate rec.

Intern AI/ML Engineer specializing in GenAI, LLMs, and agentic RAG systems

Miami, FL2y exp

“AI/LLM practitioner who built a GPT-2-like language model from scratch at the University of Maryland using PyTorch and multi-GPU distributed training, with experiment tracking in Weights & Biases. As an AI Operations intern at ScaleUp360, delivered multiple production-style AI agent automations (Gmail classification and Fireflies-to-Claude workflows that extract and assign CEO tasks) and set up measurable evaluation using test cases and classification metrics.”

Pavan Devulapalle

Screened ReferencesModerate rec.

Mid-level Software Engineer specializing in cloud platforms and AI-integrated full-stack development

Seattle, WA3y exp

“Backend engineer who built Flask-based internal APIs supporting GenAI-driven provisioning/diagnostics (Outpost/AWS Outposts-like environment), with deep hands-on optimization across Postgres/SQLAlchemy (2s to <200ms endpoint improvement). Experienced integrating ML/LLM workflows via AWS SageMaker and Bedrock, and designing multi-tenant isolation plus high-throughput Redis-backed background task pipelines (minutes to seconds).”

“Built and shipped a map-embedding SDK (published to npm) for Walmart apps, solving key performance issues with real-time streaming (WebSockets) and Canvas rendering while prioritizing developer experience. Also applies LLM/agentic patterns in production workflows—using diagnostic agents and human-in-the-loop escalation to detect and resolve issues (e.g., voice agent loops caused by RAG API failures). Has sales-engineering experience supporting enterprise renewals, including a million-dollar contract renewal while at Siemens working with Ford stakeholders.”

“Backend engineer who built a low-latency real-time transaction API in Python/Flask, with strong depth in PostgreSQL/SQLAlchemy performance tuning (time-based partitioning, indexing, connection pooling). Has production experience integrating ML scoring and OpenAI-style APIs with safety/latency controls, and designing multi-tenant isolation strategies including per-tenant pooling/caching and premium-tenant isolation.”

“Data engineer with experience at Bloomberg, UBS, and Bank of America building high-volume financial data platforms and services. Owned an end-to-end pipeline processing ~150–200M records/day (Kafka/Cassandra/S3 → Spark/PySpark → Snowflake) with strong data quality controls and Airflow reliability practices, reporting ~99% reliability and major performance gains. Also built large-scale external API ingestion with compliance-minded rate limiting, schema versioning, and quarantine/validation layers.”

Vignesh Shanmugasundaram

Screened

Junior Software Engineer specializing in full-stack development and applied ML

New York, NY2y exp

“Full-stack engineer with experience at Zoho and Amazon who has owned production systems end-to-end, including a monolith-to-microservices migration using Kafka and Cassandra that improved search latency ~25% and increased throughput without data loss. Also built a hackathon project (Buildwise) into a sold product for a construction company (AI-driven document compliance checks) and shipped an IoT-based parking availability MVP in 3 weeks.”

“Full-stack web developer with hands-on ownership of products from requirements through launch and maintenance, building across React and Node.js. Stands out for balancing product usability with technical performance, including API/database optimizations that improved performance by about 30% and shipping real-time dashboard features with scalable frontend/backend tradeoffs.”

“Engineer with a notably mature AI-native development process: uses Claude/Claude Code in a test-first, iterative workflow and has led multi-agent builds across frontend, backend, and testing. Most notably, they led development of an AI voice agent platform, creating custom agent skills and enforcing clear architectural boundaries to deliver a stable, scalable system.”

“Backend-leaning full-stack engineer with experience at Liberty Mutual and Airbnb, building high-scale insurance claims systems (1M+ monthly transactions) and consumer booking/pricing services (120K–180K daily requests). Strong in transactional data integrity, PostgreSQL performance tuning, and production operations (Docker/Jenkins/AWS), with measurable UX/performance wins including ~2.3s page loads and significant runtime failure reduction.”

“Backend/platform engineer with significant ownership at GoDaddy, where they built a real-time personalization and decisioning system that drove about $7M in annualized revenue and serves roughly 4M requests per day. Also operates as a solo engineer for a global human-rights legal-tech nonprofit, building the full platform and graph-based matching engine for 700+ partner organizations. Brings a strong blend of production backend rigor, platform thinking, and practical AI orchestration.”

Peter Greer

Screened

Senior Gameplay/AI Engineer specializing in Unreal Engine game AI systems

San Ramon, CA6y exp

“Senior Software Engineer with deep Game AI expertise (often the primary AI specialist on the team) who shipped a player-bot system in an Unreal-based battle royale to fill matchmaking gaps, reducing off-hours queue times and improving retention. Also owned complex multiplayer match-start/drop-sequence synchronization and has experience optimizing core gameplay systems (e.g., line-of-sight calculations) on Call of Duty at Infinity Ward.”

Kaochoy Saetern

Screened

Senior Unity VR/AR Developer specializing in XR platforms and immersive applications

San Francisco, CA8y exp

“Unity/C# gameplay engineer with hands-on ownership of a full VR combat system at Bad Honey Bun Games, spanning movement, combat, health, audio, lighting, and branching level flow. Shipped a Meta Quest demo that reached 10k downloads in its first month while sustaining 72+ FPS, and also brings Photon PUN2 multiplayer experience from simulation work in the oil and gas sector.”

“Backend/data engineer with hands-on production experience across Python/FastAPI services and AWS (Lambda, API Gateway, SQS, ECS) delivered via Terraform and GitHub Actions. Built Glue-to-Redshift ETL pipelines with Step Functions retry/catch patterns, schema evolution safeguards, and data quality checks; also modernized a legacy SAS monthly reporting system into Python microservices with rigorous side-by-side parity validation. Demonstrated strong SQL tuning skills with a reported improvement from 5 minutes to 15 seconds.”

Rina Thakker

Screened

Executive Product & Technology Leader specializing in consumer digital platforms and media

Darien, CT21y exp

“CTO at Grand Slam Track (track & field league) for ~2 years, owning a broad technology portfolio across digital marketing tech, IT, broadcast technology, and athlete/data management systems. Entrepreneurial operator with repeated experience assessing product-market fit using user sentiment, demand data, demographic targeting, and A/B testing; familiar with VC mechanics and looking to deepen hands-on fundraising experience via a large network and board connections.”

“Data engineer at Plaid who built greenfield, end-to-end real-time transaction pipelines and FastAPI data services for fraud detection and analytics, handling millions of events per day. Strong focus on reliability and data integrity via Great Expectations validation, Airflow-based monitoring/SLAs, quarantine/staging patterns, and robust external data ingestion with schema versioning and backfills (reported 50% fewer anomalies and ~40% fewer failures).”

Manjory saran

Screened

Senior Backend & Infrastructure Engineer specializing in cloud-native distributed systems

5y exp

“LLM infrastructure engineer who built a production-critical real-time personalization and memory retrieval system for a user-facing product, adding <100ms P99 latency while improving relevance ~20–25% and holding SLA through 3x traffic. Experienced designing tiered retrieval backends (Redis + vector store), deploying on Kubernetes with autoscaling/circuit breakers, and running rigorous observability, incident response, and agent evaluation (shadow traffic, A/B tests, regression/replay).”

“Product-minded software engineer with experience shipping AI-powered financial insights (spend forecasting, cashflow, credit optimization) and building real-time analytics systems using React/TypeScript and FastAPI. Has designed microservices with RabbitMQ/gRPC and strong observability (Prometheus/Grafana/OpenTelemetry), and also built an internal Figma plugin adopted by designers that reduced export time by 50%.”

“Backend-focused engineer who uses AI pragmatically as a force multiplier rather than a substitute for engineering judgment. They stand out for applying structured, agent-style workflows to code generation, debugging, and production log analysis while maintaining strong emphasis on correctness, performance, and reliability in backend and microservices environments.”

Neha Baadadmath

Screened

Executive Software Engineering Leader specializing in Trading, Payments, and FinTech platforms

Phoenix, AZ18y exp

“Entrepreneurially minded operator with experience in trading-platform environments who prototyped a vector-database layer to generate contextual incident narratives and reduce MTTR/escalations. Also building a non-tech venture: luxury wine distribution into India and broader Asian markets, sourcing directly from wineries with a Master of Wine and planning tier-1 launch via restaurant-owner connections while navigating complex import duties and licensing.”