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Vetted SDLC Professionals
Pre-screened and vetted.
Junior Full-Stack Software Engineer specializing in cloud-native web apps and APIs
Mid-level Site Reliability & Support Engineer specializing in Ruby on Rails platforms
Mid-level QA Test Engineer specializing in automation, API validation, and CI/CD
Senior Software QA Engineer specializing in test automation and CI/CD
Mid-level Full-Stack Engineer specializing in Java/Spring Boot microservices and React
Intern Data Scientist and GenAI Software Engineering specializing in ML and LLM evaluation
Mid-level Business Analyst specializing in data analytics and supply chain reporting
Mid-level Business Analyst specializing in financial services and analytics
Mid-level Data Analyst specializing in BI and healthcare insurance analytics
Mid-level Data Analyst specializing in business intelligence and customer analytics
Junior Software Engineer specializing in full-stack web development and machine learning
Mid-level Software QA Engineer specializing in web, API, and test automation
Senior Games QA Lead specializing in console compliance and performance automation
Senior Full-Stack Python Engineer specializing in AI/LLM-powered web applications
Senior QA Analyst specializing in web/mobile, API, and non-functional testing
Senior Full-Stack Engineer specializing in Python back-end systems and scalable web apps
Rutul Tejani
Mid-level Frontend/Full-Stack Engineer specializing in React and scalable web apps
“Frontend-focused engineer who leads end-to-end delivery of high-performance React + TypeScript products, including legal-tech client platforms and a large-scale case management dashboard handling thousands of records. Strong in SEO for SPAs, strict code quality automation, and performance work (Lighthouse 95+, 40% FCP reduction), plus disciplined rollout practices using LaunchDarkly, canary releases, and Sentry monitoring.”
Sana Khan
Mid-Level Software Developer specializing in cloud-native microservices, iOS, and ML deployment
“Backend engineer with production ERP experience deploying microservices and improving performance/reliability using a metrics-driven approach (logs, latency, error rates). Has hands-on cloud/hybrid operations across AWS and Azure with Docker/Kubernetes, and has resolved real-world mobile sync issues by tuning timeouts/retries and reducing payload sizes. Builds configurable Python services to deliver customer-specific behavior without destabilizing the core codebase.”
Bhargav Kommineni
Intern Full-Stack/ML Engineer specializing in cloud-native web apps and LLM systems
“Machine learning lab assistant at Eastern Illinois University who productionized a voice-enabled conversational AI system: redesigned it with RAG, LoRA fine-tuning (including text-to-SQL), and safety guardrails, then deployed a scalable API supporting ~1,000 daily queries. Also partnered with customer-facing teams during a BlueFi internship by building demos/APIs and accelerating releases via Terraform + AWS CI/CD automation.”
Venkata Bayarapuneni
Junior Full-Stack Developer specializing in JavaScript, Python, and cloud-deployed web apps
“Built and deployed a production LLM-powered travel assistant (Globe Trote) that automates end-to-end trip planning using a multi-step agent pipeline with RAG, external API calls, and enforced structured JSON outputs. Focused on reliability (validation, retries, fallback prompts, logging) and reported a ~30–40% reduction in irrelevant/generic responses after adding retrieval grounding.”
Dhruv Patel
Junior Full-Stack Developer specializing in React, Node.js, and AI-powered web apps
“Robotics software engineer with ROS 2 Humble/Nav2 experience on a warehouse robot fleet, focused on improving throughput in dynamic human environments. Implemented C++ local-planner and velocity-control changes using LiDAR-based motion prediction and real-time costmap tuning under a 20ms control loop, and built a Gazebo digital twin with custom failure-injection plugins plus Docker/Kubernetes deployment tooling.”
“LLM/RAG engineer at Connex AI who built and deployed a production healthcare agent to extract clinical insights from medical data/notes. Strong focus on real-world reliability—hallucination mitigation (citations, schema validation, confidence thresholds, rejection logic), custom LangChain orchestration (query rewriting, fallback paths), and production evaluation/observability—while collaborating closely with clinical SMEs to ensure clinical fit and time savings.”
Irvansyah Maulana
Junior QA Engineer specializing in manual and automation testing
“Aspiring Console QA candidate with hands-on PlayStation and Nintendo Switch testing instincts developed through deep gaming experience (edge-case inputs, handheld vs docked comparisons, online play smoothness). Has delivered under tight deadlines on a small-team project and has practical experience using internal AI tools to draft test documentation and analyze report/feedback data to identify patterns and prioritize issues.”