Vetted Unit Testing Professionals

Hitesh Bhojwani

Screened

Mid-level Robotics Software Engineer specializing in SLAM and 3D computer vision

4y exp

“Robotics software engineer focused on outdoor mobile robot localization and navigation, building ROS1/ROS2 systems with NavSat+EKF sensor fusion and custom Nav2/Costmap2D extensions for 3D obstacle clearance. Demonstrates strong real-world troubleshooting by tracing localization drift to a failing IMU connector, repairing it, and then creating sensor-health monitoring tooling; experienced taking features from Gazebo simulation through field testing to Docker/Kubernetes deployment with CI via GitHub Actions.”

Feras Alsaiari

Screened

Senior Software Engineer specializing in AWS data platforms and event-driven systems

4y exp

“Capital One engineer leading the architecture and delivery of a large-scale AWS Glue/Spark/Delta Lake batch messaging pipeline that decoupled batch from real-time flows, added multi-region failover and automated retries, and delivered ~40% AWS cost savings with ~3x performance gains. Currently building an LLM-powered Slack bot using RAG to automate message investigations by querying CloudWatch, Snowflake, and internal documentation with privacy-aware masking of NPI/PII.”

Changhee Lee

Screened

Mid-level Software Engineer and Product Manager specializing in AI and financial data platforms

Remote4y exp

“Full-stack engineer with deep Next.js App Router + TypeScript experience who has shipped and owned production features in a fashion/wardrobe/resale domain. Demonstrated measurable impact across the stack: +25% engagement, 30% faster load times, 40% fewer errors, plus durable Temporal workflows and Postgres analytics/query tuning for real-time dashboards.”

“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%.”

“Built and shipped production improvements to a Paylocity RAG-based AI assistant, redesigning retrieval into a hybrid HNSW + keyword pipeline and using tuned RRF to fuse rankings—cutting latency by ~2s and reducing token usage by ~5000. Previously spearheaded Apache Airflow integration across ETL pipelines at Acuity Knowledge Partners, creating reusable templates and automated triggers to reduce manual job monitoring.”

“Financial systems engineer who built an automated rebalance-day order reporting and analytics tool on kdb+ pipelines, cutting a high-visibility manual process from 2–3 hours to ~2 minutes and expanding it from North America to EMEA/APAC. Also proposed an early production RAG-based incident knowledge assistant trained on ServiceNow postmortems, with guardrails to scope retrieval by application.”

Chetan Mukhopadhyay

Screened

Senior Engineering Manager specializing in software quality, automation, and web/mobile platforms

Seattle, WA16y exp

“Engineering leader at Bayer Crop Science leading a Core Platform team responsible for widely used open-source TypeScript/React and mobile SDKs (npm/GitHub) embedded across 10M+ monthly active devices. Known for shipping high-performance, backward-compatible developer frameworks with rigorous release discipline (bi-weekly releases, 99.99% uptime, long streaks of zero breaking changes) and major DX wins (onboarding cut to minutes, support tickets down 82%).”

Vindhya Naidu

Screened

Mid-level Backend Software Engineer specializing in Java/Spring microservices and FinTech

Austin, TX5y exp

“Backend engineer with Apple experience who owned production platform improvements end-to-end, including a Redis caching layer that cut API latency ~35–40% and reduced DB load. Has hands-on on-call/incident response and observability (CloudWatch), plus experience scaling Docker/Kubernetes microservices and operating Kafka-based telemetry pipelines with schema evolution, deduplication, and replay/backfill handling.”

“Engineer with hands-on experience shipping production Python integrations and designing for reliability from day one, including idempotency, retries, dead-letter handling, contract checks, and full observability. Also brings web automation experience with Puppeteer and has implemented high-availability failover using load balancer liveness checks, backup environments, and cold standby architecture.”

“Primary engineer at Customer Insights AI who built an end-to-end Python pipeline for 340B drug pricing compliance, using ML to detect suspicious pharmaceutical claims and benefit diversion. Stands out for combining healthcare compliance domain knowledge with production reliability practices, and for turning ambiguous analyst-driven review processes into automated workflows that cut manual review by 70%.”

“Internship experience at TikTok and nCino, with hands-on work spanning production Python data pipelines, recommendation-system feature workflows, Salesforce Apex automation, and flaky UI automation for a live stock recommendation platform. Stands out for a reliability-focused approach: anticipating failure modes, instrumenting observability, and turning ambiguous business processes into maintainable automated systems.”

“Postdoctoral/PhD researcher focused on Alzheimer's disease who has built scalable end-to-end AI systems across pathology imaging, transcriptomics, and longitudinal neuroimaging. Particularly strong in turning novel research ideas into robust Python pipelines on GPU/HPC infrastructure, with pathologist-facing impact and scientifically novel findings such as image-derived disease severity trajectories and subtype discovery.”

Rucha Joshi

Screened

Junior Software Engineer specializing in full-stack and backend development

Austin, TX2y exp

“Builder of multiple zero-to-one consumer applications, including an anonymous writing feedback tool with a Gemini-powered chatbot, a dietary-profile recipe product using LLM-based substitutions, and a live-updates Sports Hub. Stands out for hands-on full-stack execution, iterative AI experimentation, and a quantified 80% reduction in time users spent finding recipe-compatible ingredients and options.”