Vetted Unit Testing Professionals

“Firmware architect/lead engineer for automotive LiDAR sensors, designing RTOS-based, layered firmware and solving high-throughput real-time constraints using DMA and lock-free buffering. Built ROS nodes to bridge embedded sensor output to higher-level perception (point clouds, diagnostics, configuration) while isolating real-time logic in firmware. Established an end-to-end CI/CD pipeline with GTest unit tests plus SIL/HIL automation and Dockerized build/test environments.”

“Software engineer with strong end-to-end ownership of search and listing systems (React/TypeScript frontend with Node.js + Spring Boot backends), focused on shipping fast while managing risk via feature flags, testing, and metrics. Demonstrated measurable UX/performance wins (reduced latency and search abandonment) and built internal observability tooling (dashboard + alerts) that improved incident response. Experienced with microservices reliability patterns including idempotency and dead-letter queues.”

“Senior frontend engineer with experience leading high-impact React/TypeScript products at HelloFresh and CAA, including an A/B-tested onboarding flow shipped across multiple international brands. Modernized a legacy .NET frontend to Next.js using SSR and performance techniques (caching/memoization/lazy loading) and implemented robust testing/monitoring (Cypress, Honeycomb, GA) in fast-paced, production-deploy environments.”

“Software engineer with Capital One experience contributing to shared internal “open-source style” JavaScript/React/TypeScript libraries (component library and hooks/utilities). Drove measurable performance gains (~25% improvement) by refactoring hooks to prevent unnecessary re-renders, and improved adoption via stronger documentation, testing (Jest), semver discipline, and code review/PR workflows; also stabilized a backend service by adding monitoring and automated tests in an unstructured project.”

“Built a production AI-driven QA automation platform using a multi-agent architecture (MCPs + LangGraph) to run parallel website tests across multiple device environments via automated image building and containerization. Currently collaborating with restaurant operators and managers to deliver an agentic restaurant analytics system, emphasizing deep domain discovery with non-technical stakeholders.”

“Backend/DevOps-focused engineer with healthcare and financial systems experience, including an ICU readmission risk platform delivering real-time ML scores via a secure FastAPI service (PyTorch model serving, PostgreSQL, Celery/Redis) deployed on AWS with strong observability. Has hands-on Kubernetes GitOps delivery (Helm, ArgoCD, HPA) and has supported a JPMC on-prem-to-AWS microservices migration using phased validation and blue-green cutovers, plus Kafka/Avro streaming for real-time transaction processing.”

“Real-time 3D/C++ developer with hands-on engine-level systems work, including a 3D positional audio/Doppler pipeline stabilized against frame-rate jitter via fixed-timestep + interpolation architecture. Built a runnable 3D engine project featuring custom collision detection/response (AABB, SAT, sphere) with unit and edge-case testing, and has UE5 multiplayer movement experience implementing a custom sprint mode using Character Movement (SavedMove, intent prediction).”

“Full-stack engineer with startup experience who owned end-to-end features on Impact’s Hiring Solutions platform, including a hiring inbox spanning React UI and Postgres data models; the product helped drive 500+ jobs filled shortly after launch. Comfortable designing modern React/TypeScript + Node architectures (GraphQL, testing, migrations) and operating on AWS (RDS, EC2/Fargate, S3, Datadog, CircleCI). Also founded their own startup (Bibbr) and made early-stage stack/infrastructure decisions under high ambiguity.”

“Software engineer with hands-on experience building a distributed ticketing system on AWS (Terraform, Go, MySQL) focused on high-concurrency reliability (locks/queues to prevent duplicate ticket confirmations) and load-tested performance. Also independently owned and shipped an Airflow automation script to stop/restart workflows during deployments with email notifications, reducing manual operational effort.”

“Full-stack engineer with fintech/trading domain experience (Fidelity) and startup SaaS CRM/billing platform work (Zoho), building real-time portfolio analytics and trade-processing systems. Strong in microservices, event-driven architectures (Kafka/WebSockets), and AWS/Kubernetes operations with measurable performance gains (~34–35% latency reduction) and maintainability improvements (~40% faster deployments). Targeting a founding full-stack engineer role in NYC with meaningful equity.”

Hangquan Zhao

Screened

Senior Software Engineer specializing in connected vehicle platforms and real-time data systems

Mountain View, CA4y exp

“Open-source maintainer of KafkaJSUI, a Vue.js-based Kafka browser UI, focused on making large-topic exploration fast and responsive. Delivered major performance wins (incremental fetching, virtualized lists, WebSocket streaming, backpressure, Web Worker offloading) cutting load times to sub-200ms, and also strengthened CI and developer documentation while handling community-reported issues end-to-end.”

Pandari G

Screened

Mid-level Machine Learning Engineer specializing in Generative AI and RAG systems

San Francisco, USA5y exp

“GenAI/LLM engineer with production deployments in both fintech and retail: built an AI-powered mortgage document analysis/automated underwriting pipeline at Fannie Mae (OCR + custom LLM) cutting underwriting review from 3–4 hours to under an hour with privacy-by-design controls. Also helped build Sephora’s GenAI product advisory bot using LangChain-orchestrated RAG (Azure GPT-4, Azure AI Search, MySQL HeatWave vector search), focusing on grounding, evaluation, and compliance-aware architecture choices.”

Khoa Nguyen

Screened

Junior Software Engineer specializing in Python, AWS, and data/ETL systems

Washington, USA1y exp

“Data/ETL-focused engineer with Amazon experience building and deploying AWS-based pipelines that became the primary source of automated customer feedback insights (processing millions of records daily). Demonstrated strong incident troubleshooting across software/host/network layers using CloudWatch, traces, and metrics, plus hands-on stakeholder and on-site operator collaboration to translate reporting needs into star-schema data models and tailored Python ETL logic.”

Ahmed Atallah

Screened

Senior Controls & Localization Engineer specializing in autonomy, sensor fusion, and MPC

Troy, Michigan12y exp

“Robotics software engineer focused on state estimation and localization reliability, with deep hands-on EKF tuning/validation using DGPS ground truth and integrity-risk-based uncertainty calibration. Built middleware-agnostic interfaces with ROS wrappers to enable repeatable ROS bag playback testing, and implemented CI at Caterpillar to automatically build the localization stack and run unit tests plus bag-based regressions before merge.”

“Infrastructure/operations engineer with deep IBM Power/AIX experience (AIX 7.x, VIOS, HMC/vHMC) managing ~15–25 LPARs across production and DR, including live DLPAR changes and structured performance troubleshooting. Also hands-on with PowerHA/HACMP incident recovery and failover testing, plus broader DevOps delivery building Jenkins CI/CD for containerized microservices and Terraform/Ansible IaC across AWS and Azure, and leading Solaris SPARC to x86 migration cutovers.”

“Data engineer at Capital One building AWS-based real-time and batch pipelines and backend data services for financial/fraud use cases. Has owned end-to-end pipelines processing millions of records/day, implemented dbt/Great Expectations quality gates, and tuned Redshift/Snowflake workloads (cutting query latency ~22–25% and reducing pipeline failures ~30–40%) while supporting 15+ downstream consumers.”

Sai Naveen Masadi

Screened

Senior .NET Full-Stack Developer specializing in cloud-native enterprise apps

Irving, TX5y exp

“Full-stack TypeScript engineer who built and operated a production order/inventory platform (React + NestJS/Node + PostgreSQL) with Redis and RabbitMQ for performance and background workflows. Emphasizes correctness in production via idempotency, retries/backoff, DLQs, and observability, and has also delivered external-facing REST APIs (Swagger, versioning, JWT/RBAC) plus resilient checkout browser automations using Playwright/Puppeteer.”

Shram Kadia

Screened

Mid-level Software Engineer specializing in backend systems, cloud-native apps, and AI platforms

Santa Clara, CA4y exp

“Backend/full-stack engineer who has owned production systems end-to-end, including a Dockerized Node.js/TypeScript probabilistic fault-tree analysis service for nuclear safety research deployed on AWS. Also built and operated a FastAPI-based RAG pipeline over 200+ PDFs using FAISS, focusing on low-latency, idempotent workflows and strong observability; experienced with API design and Playwright E2E automation across React/Angular projects.”

Yash Rangucha

Screened

Mid-level Software Engineer specializing in backend microservices and real-time streaming

Illinois, USA4y exp

“Built and owned an end-to-end LLM-powered enterprise retrieval pipeline at ServiceNow, spanning ingestion of structured/semi-structured sources through vector retrieval and real-time API serving. Focused heavily on reliability and quality (multi-stage validation, monitoring, evaluation pipelines) while also driving performance improvements (~35% faster responses) via caching, async processing, and SQL/query optimization.”

“Built and shipped an LLM-powered support assistant for a fintech payment reconciliation system that automated failed-transaction analysis at scale. Delivered measurable production outcomes (40% less manual reconciliation, 25% better detection accuracy, 99%+ uptime) and implemented strong reliability patterns (Prometheus/Grafana monitoring, retries/fallbacks, idempotency, Resilience4j circuit breakers) plus iterative retraining driven by real error analysis.”

“ML/AI engineer with hands-on experience building production healthcare AI systems across predictive modeling and GenAI. They built an end-to-end patient risk prediction platform and a RAG-based clinical summarization feature, combining strong NLP/LLM skills with AWS deployment, monitoring, drift detection, and reusable Python service design to deliver measurable clinical and operational impact.”

“Backend engineer with strong payments and high-stakes transaction experience, including owning an Apple Pay/Google Pay integration via Stripe end-to-end in production for 100,000+ users. Particularly compelling for teams that need someone who can balance speed, security, and reliability in checkout or other sensitive backend workflows, and who has hands-on incident ownership in production.”

“Currently at Berryble AI, this candidate is building an LLM-based real-time interview analysis engine using FastAPI, WebSockets, fine-tuned models, and GCP/Cloud Run. They stand out for using AI and agent workflows pragmatically to accelerate development while keeping human ownership over architecture, security, reliability, and maintainability, and they are also pursuing a master's in applied machine learning.”

“ML/AI engineer with strong production depth across classical ML, MLOps, LLM/RAG, and scalable Python data platforms, with experience at Cisco and Accenture. Stands out for tying technical decisions to measurable business outcomes, including $1.2M annual savings, 40% faster support resolution, and broad internal adoption of shared engineering frameworks.”