.png){kind=logo}
Vetted Distributed Systems Professionals
Pre-screened and vetted.
Keerti Chaudhary
Intern Full-Stack Engineer specializing in AI-powered products
“Software engineer (internship experience) who built and owned an AWS serverless multi-user “challenge” feature end-to-end (UI + REST APIs + DynamoDB + deployment), delivering measurable gains in latency (-30%), debugging time (-50%), and join drop-offs (~-30%). Also productionized a multilingual RAG-based QA system with vector retrieval and guardrails, improving accuracy to ~85% and driving ~20% DAU growth.”
CharanKumar Pathakamuri
Entry-Level GenAI/LLM Engineer specializing in agentic systems and RAG
“LLM/AI agent engineer with consulting/contract experience (Kanhaiya Consulting LLC) who deployed a production AI agent to automate BIM list workflows end-to-end—from database understanding and data cleaning to automated visualizations/dashboards. Worked around restricted real-time data access by generating synthetic data and improving outputs via supervised fine-tuning, and uses AWS-based LLMOps observability (Opic/OPEC) plus hybrid retrieval (vector+BM25 with reranking) to optimize relevance, latency, and cost.”
Dhruv Bansal
Intern Software Engineer specializing in backend systems and distributed data pipelines
“LLM engineer with production experience building end-to-end document processing workflows that unify layout analysis, OCR, and downstream LLM reasoning. Has implemented reliability features (retries, robust error handling, OpenTelemetry logging) and built agentic systems using LangChain/CrewAI, including a student research-paper assistant, while collaborating closely with PMs and non-technical end users to reduce technical debt and simplify architectures.”
Vishnu Priyan Sellam Shanmugavel
Mid-Level Applied AI Engineer specializing in LLM services, RAG, and OCR/NLP extraction
“Backend/platform engineer who built and evolved a large-scale healthcare document processing system (OCR + LLM orchestration) in Python/FastAPI on Google Cloud (Cloud Run, GCS, Firestore), processing ~1.5M files per batch and tens of millions overall. Emphasizes reliability and operational safety via deterministic IDs, idempotent state machines, strong observability, and self-healing reconciliation, plus disciplined migrations using dual-run validation and incremental rollouts.”
“Software engineer with experience spanning healthcare middleware (patient records + insurance integration) and an AI fantasy football product built with React/TypeScript, Firebase, API gateways, and pandas-based data pipelines. Has hands-on microservices scaling experience (latency mitigation, async migration, state-based redesign) and built an internal feature-toggle dashboard that improved demo efficiency and sales outcomes.”
Tanvi Kulkarni
Intern Full-Stack Engineer specializing in Java, React, and cloud-native backend systems
“Frontend-focused engineer with startup experience (SmartPath, OPC AI) who owned and evolved an internal React/TypeScript component library treated like OSS—refactoring core form and API wrapper modules for stability, type safety, and smaller bundles. Comfortable diagnosing production issues via logs/API traces and shipping end-to-end fixes with tests and documentation, including internal workshops to drive adoption.”
Sahilsingh Harcharansingh Khalsa
Junior Full-Stack/Product Engineer specializing in Next.js, TypeScript, and AWS backends
“Full-stack engineer with startup-style end-to-end ownership, recently shipping a production dashboard at Find Me LLC using Next.js App Router/TypeScript with Supabase + Azure Blob Storage for secure asset/document uploads. Strong server-first React performance mindset and hands-on Postgres modeling/query optimization (EXPLAIN ANALYZE), plus experience building resilient AWS event-driven workflows with idempotency, retries, and DLQs.”
SaiLokesh Gayam
Mid-level Full-Stack Software Engineer specializing in AI and RAG systems
“Backend/AI engineer who built an enterprise RAG chatbot over 40,000+ technical documents, owning the system from ingestion and retrieval design through launch, optimization, and incident prevention. Stands out for treating LLM reliability as a data, retrieval, and observability problem—delivering 90%+ benchmark accuracy, ~50% fewer hallucinations, and major gains in lookup speed and latency.”
Shabad Mathoun
Entry-level Full-Stack Developer specializing in web platforms and applied systems research
“Backend-focused engineer who built Codesdev V1.0 end-to-end, a cloud-native IDE with secure Docker-based code execution across 8 languages and a custom PostgreSQL JSONB virtual file system achieving 34ms retrieval. Stands out for pragmatic early-stage decision-making, hands-on ownership from architecture through incident resolution, and a strong focus on security and low-latency backend design.”
Nikita Sipeikin
Mid Backend Java Developer specializing in high-load FinTech systems
“Java developer with hands-on experience using AI coding tools heavily in day-to-day development, estimating roughly 60% AI-generated output in a recent shipped feature. Brings practical debugging and testing experience, including performance testing and resolving Spring Boot circular dependency issues through architectural changes.”
Ali Arsalan
Senior Software Engineer specializing in frontend architecture and scalable e-commerce platforms
“Founding engineer at Salla who helped rebuild a monolithic Laravel merchant dashboard into a React/TypeScript Single-SPA microfrontend platform used by thousands of online stores. He combines hands-on frontend architecture, real-time operational dashboard design, and cross-team API/platform leadership, and says he built about 70% of the merchant-facing features in the system.”
sandeepreddy bimidi
Entry-level Full-Stack Software Engineer specializing in AI/ML and cloud systems
“Software engineering intern who built and deployed a full-stack telemedicine platform (React/Node/MongoDB) used daily in a pediatric clinic, incorporating PyTorch-based predictive features. Demonstrated strong customer-facing iteration and production performance debugging—resolved a live slowdown by indexing/optimizing MongoDB queries and adding caching, improving response times by ~50%.”
Neil Sharif
Senior Go Engineer specializing in low-latency FinTech platforms
“Backend/distributed-systems engineer with 9 years of Go experience, focused on financial-services platforms where performance, reliability, and regulatory auditability are critical. He has built low-latency market data infrastructure (p99 under 8ms) and optimized compliance/reporting systems used by finance and audit teams, combining strong systems design with practical production operations.”
Keya Patel
Entry-level AI/ML Engineer specializing in RAG chatbots and backend systems
“Student technologist building production-oriented AI products, including a college guidance chatbot for Track2College and a voice-based travel assistant. Strong hands-on experience with RAG systems, FastAPI backends, TypeScript frontends, retrieval evaluation, and tool-using LLM workflows, with a clear focus on grounded, reliable user experiences.”
Md Iqbal Hossain
Mid-level AI & Computer Vision Engineer specializing in edge robotics perception
“Master’s thesis engineer who built and deployed a continuous real-time perception + state estimation + control loop under tight latency constraints, owning both software architecture and hardware integration. Strong ROS 2 fundamentals with a systems-first approach—stabilizes robotic behavior by instrumenting, logging/replaying real data, and fixing timing/synchronization issues rather than treating failures as purely algorithmic.”
Swapnil Sanjay Pawar
Junior Full-Stack Software Engineer specializing in GenAI and web platforms
“AI/software engineer with hands-on experience deploying an LLM-powered quiz generation platform for students, integrating Python services with Gemini APIs plus frontend and database components. Emphasizes production-grade reliability through observability, schema validation, async processing, and performance tuning under high concurrency, and has collaborated with product/operators (e.g., at Colombo AI) to translate real-world constraints into scalable technical solutions.”
ROHITH DAMARLA
Mid-level Backend Engineer specializing in high-scale systems and LLM pipelines
“Open-source-focused TypeScript/JavaScript engineer who built a lightweight Node.js utility library to standardize LLM-agent message formatting, tool invocation, and safe schema-validated JSON outputs. Emphasizes composable abstractions, real-world performance profiling/benchmarks, and strong community feedback loops (GitHub issues, structured errors, logging hooks). Also did research at Syracuse University on converting natural language into structured JSON with validation layers.”
Balaji Namala
Junior AI Engineer specializing in LLM systems, RAG, and scalable cloud AI
“Built and shipped production LLM agents for real-time, high-concurrency conversational systems, including a RAG-based pipeline with dynamic multi-provider routing and failover that achieved 99.99% reliability and sub-800ms latency. Also architected a UAV telemetry chatbot with tool-calling (anomaly detection/summarization), strict schema validation, and robust eval/monitoring loops, cutting tool-call errors by 30% and reducing operational costs by 90%.”
Thota Rajkumar
Junior Cloud & AI Infrastructure Engineer specializing in Agentic AI and AWS
“Built and deployed a production AI career-advice agent designed to combat unreliable/generic LLM guidance by grounding outputs in retrieval-first RAG over resumes/job/hiring data, with multi-step reasoning, structured memory, and evidence-only prompting to reduce hallucinations. Implemented the system with LangChain/Python and deployed on AWS as scalable microservices orchestrated via REST and asynchronous calls, iterating closely with career coaches and students.”
Jeevan Hebbal Manjunath
Junior Robotics & Machine Learning Engineer specializing in autonomous systems
“Robotics engineer leading development of a Physical Reservoir Computing controller for a pneumatic soft robotic arm, owning everything from automated data collection and leak-testing automation to hardware design/manufacturing and cross-lab integration with Virginia Tech. Built ROS 2/DDS-based multi-robot systems integrating OptiTrack, a lab quadruped, and a UR5e, and pairs simulation (Gazebo/MuJoCo) + PPO RL training with production-ready tooling (Docker, CI/CD, Flask dashboards, RAG chatbot portfolio).”
Vitor Souza
Senior Game Developer specializing in multiplayer, XR/VR, and real-time networking
“Unity/C# gameplay engineer who has owned end-to-end systems for live-service AR and shipped VR (Meta Quest) and mobile titles. Built a hybrid LLM-driven real-time NPC interaction pipeline (STT/LLM/TTS) with streaming SSE, strict JSON contracts, and state-machine execution for stability, plus a custom UDP/TCP authoritative multiplayer stack deployed on AWS EC2 with live monitoring and rapid hotfix capability.”
Dhairya Chhabra
Mid-level Full-Stack Software Engineer specializing in distributed systems
“Full-stack engineer who built WordCon, an AI-powered vocabulary learning platform, end-to-end across React/Next.js, Python, AWS, and GenAI services. Particularly strong at turning ambiguous AI product ideas into structured, scalable systems by combining deterministic learning logic with LLM-powered personalization, and has additional experience modernizing legacy PHP systems into React/Node architectures.”
Xuebin Dong
Mid-level Software Engineer specializing in distributed systems and healthcare data platforms
“Full-stack and AI engineer who built both a large-scale clinical imaging dataset exploration engine and DMP Chef, an open-source LLM product for generating funder-compliant Data Management Plans. Stands out for combining strong product ownership, data-intensive backend architecture, and practical LLM systems work with retrieval, structured outputs, evals, and human-in-the-loop compliance safeguards.”