Vetted Engineering Professionals

“Candidate brings practical GenAI engineering experience with a disciplined approach to AI-assisted development. They have designed lightweight multi-agent workflows for a RAG-based support copilot, including retrieval, relevance validation, response generation, and groundedness checks to reduce hallucinations.”

“Built and stabilized an AI-assisted document processing workflow for Possible Finance that supported underwriting without automating final loan decisions. Stands out for combining practical LLM integration skills with strong guardrails, validation, and fallback design in a financial workflow, delivering roughly a 35% reduction in document processing time.”

“Built and shipped an end-to-end autonomous telemetry and log-triage product that combined LLM-based anomaly analysis, strict typed validation, and a React observability UI. Particularly compelling is their focus on making non-deterministic AI reliable in production at scale—500,000 daily requests and 99.9% uptime—while also translating complex AI output into a usable experience for non-technical teams during live outages.”

Shivoham Angal

Screened

Entry-level Backend Software Engineer specializing in AI and cloud systems

Remote, New York1y exp

“Backend-focused engineer who built a hackathon trading vault (AntiSwan) integrating the Polymarket CLOB client and applying the Kelly Criterion for allocation decisions. In an internship at StartupU, owned pre-launch monitoring by building Azure dashboards and Terraform/KQL-driven alerts with Microsoft Teams webhook routing, and previously automated a DynamoDB cross-region migration with integrity checks.”

“Operations-to-engineering builder who turned a real dispatcher pain point into a live fleet-tracking and routing prototype using React, FastAPI, WebSockets, and mapping/routing tools. Also building AI workflow-automation products for non-technical office users, combining deterministic validation, sandbox replay, and LLM-assisted workflow splitting. Especially interesting for teams that value scrappy zero-to-one product ownership and practical automation.”

Wei-Hsien Wang

Screened

Entry-level AI Engineer specializing in full-stack generative AI systems

San Jose, CA1y exp

“AI/full-stack product engineer who has shipped both user-facing and internal LLM products, from a photo-to-music recommendation app to an experimentation agent at Azazie. Stands out for combining modern app development with production-grade agent and GraphRAG systems, including a 500k+ email analysis platform and measurable impact like 3x experiment velocity, 75% setup-time reduction, and 65% faster task discovery.”

Cassandra Pizarro

Screened

Mid-level Software Engineer specializing in frontend and integrations

Mountain View, CA7y exp

“Frontend-leaning product engineer with strong ownership in fintech integrations, including leading the first global PayPal integration on QuickBooks and enabling 20,000+ non-U.S. users across UK, Canada, and Australia. Brings a mix of React/TypeScript architecture, API collaboration, and domain depth in accounting workflows like VAT and Chart of Accounts mapping.”

“Senior frontend engineer with 8+ years of experience spanning Verizon and 7-Eleven, focused on developer platforms, design systems, and real-time operational products. Built framework-agnostic component libraries and large-scale React/TypeScript architectures that reduced feature development time by 30%, improved UI satisfaction by 40%, and cut onboarding time by 25-30%. Particularly strong in WebSocket-driven GenAI experiences, observability dashboards, and cross-functional API/platform leadership.”

“Full-stack engineer who has built both a TypeScript-based HR/payroll platform and a production agentic AI support system end to end. Stands out for combining strong product judgment with deep LLM systems thinking: RAG architecture, confidence-based routing, evals, observability, and human-in-the-loop design in a greenfield environment.”

Zack Pagano

Screened

Junior Full-Stack Software Engineer specializing in FinTech and data platforms

San Francisco, CA3y exp

“Engineer in a highly regulated banking environment who has built both a full-stack digest product that cut notification volume 40% and an internal LLM-powered on-call assistant that reduced triage time by 30%+. Stands out for combining strong AWS/serverless and TypeScript architecture skills with careful AI safety, observability, and compliance-minded design.”

“Backend-leaning full-stack engineer with PayPal experience building payment orchestration, settlement, and merchant risk systems at production scale. Stands out for combining cloud-native AWS delivery, database/query performance tuning, and reliability work in event-driven microservices, including a monolith-to-microservices migration that doubled deployment frequency and cut incident response time by 40%.”

Manoj Shinde

Screened

Senior Full-Stack Engineer specializing in cloud-native AI and FinTech systems

San Francisco, CA9y exp

“Full-stack engineer who has owned customer-facing reporting products end to end and also helped ship MemberGPT, an AI assistant for financial users. Brings a practical mix of React/TypeScript and Java/Spring Boot experience, plus hands-on LLM integration, retrieval grounding, evaluation, and production monitoring in a higher-trust financial context.”

Thomas Toan

Screened

Senior Frontend Software Engineer specializing in regulated and high-performance web applications

San Mateo, CA11y exp

“Frontend/product engineer who has owned high-impact surfaces across video streaming, edtech analytics, and regulated healthcare platforms. Notable work includes rebuilding a clinical trial forms system with strict TypeScript standards, designing real-time livestream engagement features, and shipping a lightweight PIP player that improved Core Web Vitals by avoiding heavy SDK load on initial page render.”

Akhila Gadige

Screened

Mid-level Full-Stack Developer specializing in Python, Java, cloud, and GenAI

Remote4y exp

“Backend-leaning full-stack engineer who has built and operated high-throughput GPU telemetry and task/event platforms using React, FastAPI, PostgreSQL, Redis, Celery, and Kubernetes. Stands out for hands-on ownership of production performance at scale, including partitioning 100M+ row tables, fixing timeout bottlenecks, and delivering measurable gains like 3x throughput and 95% fewer timeout errors.”

“Backend/platform engineer who has built and run production Python/Flask + Kafka microservices processing RFID and camera/RFID fusion streams for near-real-time retail cart updates at ~4–5M events/day. Strong in reliability/performance debugging (p99 latency, Kafka lag, Cosmos DB RU hot partitions) with measurable impact including ~30% database cost reduction, and has also shipped an end-to-end vulnerability scanning workflow with DynamoDB-backed state, idempotency, and robust retry/verification guardrails.”

“Robotics software engineer with hands-on GPU/CUDA vision work (solo-built a 4-fisheye panorama stitcher using camera intrinsics/extrinsics) and mapping/localization expertise, including radar-driven pose-graph mapping optimized with Ceres. Strong ROS background (Cartographer, AMCL, TEB) and demonstrated localization improvements by biasing AMCL with Cartographer to reduce drift; experience shipping modules deployed across large robot/vehicle fleets (e.g., retail scanning robots and automotive).”

“Robotics software engineer focused on autonomous eVTOL operations, including simulated autonomous ship deck landing using ROS2 Humble with perception (AprilTags) and motion planning under aircraft dynamics constraints. Has hands-on experience with multi-robot coordination, SLAM sensor-fusion fixes, and distributed robot networking (LTE + VPN), plus embedded data capture on Jetson AGX Orin and advanced control methods (MPC/CBF, differentiable learning).”

“Full-stack engineer who built an LLM-powered productivity web app (LifeOS) end-to-end with TypeScript/Next.js, Prisma, and Postgres, emphasizing fast iteration with stable API contracts and an isolated AI service boundary. Also built a security/compliance login-verification workflow at Medpace used within an internal admin portal for thousands of employees, and has AWS experience orchestrating batch GPU workloads with robust retry/idempotency patterns.”

“Robotics software engineer with hands-on experience delivering autonomous pick-and-place: built a depth-camera perception pipeline for tiny (15–20mm) parts using YOLO+SAM segmentation feeding Open3D ICP/RANSAC pose estimation and validated it end-to-end with ABB YuMi/RobotStudio. Strong ROS 2 integrator (Nav2, SLAM Toolbox, MoveIt2, Behavior Trees) who has debugged real TurtleBot3 odometry/latency issues and redesigned system architecture to improve reliability.”

“Capgemini engineer who helped take a travel insurance platform from prototype demos to a stable production system by clarifying requirements, hardening API contracts, and adding validation/logging to handle real customer data and external integrations. Experienced in real-time troubleshooting of complex workflows (including LLM/agentic-style workflows) through strong observability practices, and in leading practical developer-focused demos that accelerate client integration and adoption.”

“Unity gameplay/AI engineer with driving-simulator experience who re-architected state-based AI using multithreading (including a threaded 2D collision/location checker) to nearly double AI traffic while improving frame rate. Has shipped on a Photon-networked title (Frankie's Revenge / RoboRevengeSquad) and is comfortable debugging tricky multiplayer spawning/movement issues with practical client-server test setups.”

“AI/LLM engineer with production experience at Charles Schwab building a RAG-based assistant to help 5,000+ reps answer complex financial policy questions. Implemented a multi-layer anti-hallucination approach (GNN-driven ontology/graph retrieval + citation-only answers) and compliance-focused guardrails (Azure AI Content Safety) in partnership with audit/compliance stakeholders.”

“Interned at Zonda where he built an AI-driven semantic search solution over ~280M housing/builder records. Iterated from local LLMs via llama.cpp quantization to a vector-embedding retrieval system, then boosted semantic accuracy with a custom spaCy NER layer and re-ranking, optimizing for latency through precomputation. Collaborated with economics-focused stakeholders to reduce manual document/paperwork time by enabling natural-language search over internal data.”

“Engineer with banking and industrial/IoT experience who has deployed a payment-processing microservice with zero downtime, handling Protobuf schema evolution and sensitive data migration via dual-write/checksum techniques. Demonstrates strong cross-stack troubleshooting (pinpointed intermittent distributed timeouts to a failing ToR switch port) and customer-facing Python ETL customization using plugin-based parsers and Pydantic validation, plus hands-on monitoring/alerting improvements with operators.”