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Vetted Engineering Professionals in the Raleigh-Durham
Pre-screened and vetted in the Raleigh-Durham.
Popular Titles
Mid-level Full-Stack Engineer specializing in Java/Spring Boot, React, and cloud-native microservices
Senior SDET / QA Automation Engineer specializing in UI, API, and mobile test automation
Senior Software Engineer specializing in full-stack web apps and LLM/RAG systems
Mid-Level Backend & Data Engineer specializing in cloud infrastructure and analytics
Senior Full-Stack Python & AI Engineer specializing in FinTech and real-time platforms
Senior Full-Stack Engineer specializing in Unity, multiplayer networking, and VR/mobile
Manav Kamdar
Intern Full-Stack Software Engineer specializing in web apps, cloud microservices, and AI tooling
“Robotics/embedded candidate who built an IoT smart shoe for visually impaired users, implementing real-time obstacle detection with ultrasonic sensors and haptic feedback on Arduino. Has practical ROS experience (RViz/Gazebo) and improved reliability in distributed systems by hardening an Arduino-to-ROS serial protocol with framing, strict parsing, and sensor-noise filtering; also containerized ROS environments with Docker for reproducible simulation and onboarding.”
Senior Electrical Engineer specializing in energy storage and power systems
Intern Embedded Software Engineer specializing in robotics, networking, and edge AI
Director-level QA Engineering Lead specializing in test automation and DevOps
Entry-Level Full-Stack & ML Engineer specializing in web apps and predictive analytics
Junior Software Engineer specializing in Java microservices and cloud deployment
Mid-level Software Engineer specializing in backend systems, microservices, and AI pipelines
Mid-Level Software Engineer specializing in full-stack and cloud-native systems
Jack Storment
Senior Backend Developer specializing in AWS cloud-native systems and data pipelines
“Backend/data engineer with aerospace telemetry and reporting experience across RTX and other orgs, spanning Python/FastAPI microservices, AWS serverless/containers, and AWS Glue-to-Redshift analytics pipelines. Has led legacy modernization with parallel-run parity validation and incremental rollout, and demonstrates strong operational ownership (monitoring, incident response, and cost optimization).”
Junior Full-Stack Software Engineer specializing in web apps and data-driven products
Mid-level QA/Test Engineer and Unity VR Developer specializing in immersive training modules
Mid-level Backend Engineer specializing in Node.js/TypeScript and scalable systems
Junior Software Engineer specializing in Java, Python, and web APIs
Junior Software Engineer specializing in full-stack and data-driven cloud systems
Junior AI Software Engineer specializing in healthcare NLP and FHIR data pipelines
Shaktisharan Rajure
Mid-level Full-Stack Engineer specializing in backend APIs on AWS (Healthcare & FinTech)
“Backend engineer who evolved and migrated a real-time smartwatch telemetry ingestion/analytics platform in a healthcare context, focusing on reliability under poor network conditions. Experienced with Python/FastAPI and Java microservices, PostgreSQL performance tuning, and production-grade security (JWT/OAuth, RBAC, RLS) with incremental rollout and parallel-run migration strategies.”
Shaktisharan Rajure
Mid-Level Full-Stack Engineer specializing in microservices and cloud APIs
“Software engineer who builds workflow-centric products end-to-end, including a customer-facing module on the Trident AI content platform and an internal content workflow tool adopted as the default process. Strong in TypeScript/React + FastAPI architectures and in scaling event-driven microservices with RabbitMQ, emphasizing reliability (idempotency, DLQs) and observability (correlation IDs) to reduce outages and debugging time.”
Navyatej Tummala
Junior Backend Engineer specializing in cloud APIs and AI-enabled systems
“Built and shipped "OnCall Copilot," a production Slack-based RAG assistant that answers on-call questions from runbooks and postmortems with citations using a FAISS vector index. Emphasizes reliability and measurable performance via strict guardrails ("no evidence, no answer"), evaluation metrics, drift monitoring, and operational hardening with Docker, logging, health checks, and offline fallback.”