Vetted Indexing Professionals

“Frontend-leaning full-stack engineer who described owning an artist search and detail experience across UI, backend integrations, and data modeling. They show practical strength in scalable React architecture, TypeScript safety, and performance tuning, with a product-minded approach to shipping 0→1 features quickly and iterating after launch.”

“Robotics-focused engineer with ROS 2 experience who has built and debugged real-time, distributed control/orchestration systems under production-like latency and safety constraints. Led platform changes at Persona for a real-time verification orchestration system using deterministic state machines and async workers, and has hands-on experience stabilizing multi-robot navigation/SLAM behavior using rosbag, RViz, and stress testing in simulation (Gazebo).”

Venu Dave

Screened ReferencesStrong rec.

Junior Software Development Engineer specializing in backend data platforms and LLM applications

New York, NY3y exp

“Amazon internship experience building and shipping an end-to-end NL-to-SQL system: ingested/normalized metadata across 60+ internal tables, added rigorous multi-layer validation for LLM-generated SQL, and served it via a FastAPI backend for engineers—driving 90%+ faster dataset discovery and ~70% lower effort to access data. Also built an early-stage RAG-based healthcare assistant, iterating on chunking, embeddings, and retrieval to improve answer quality post-launch.”

“Python backend engineer focused on high-throughput document/PDF processing systems, building end-to-end pipelines that extract structured content for downstream NLP use cases. Demonstrates strong practical MLOps-adjacent infrastructure skills: Kubernetes deployments, GitLab CI, GitOps workflows, and an incremental migration to AWS using EC2/Lambda tradeoffs. Deep hands-on optimization experience (selective OCR, layout-aware extraction, parallelism, caching, idempotency, and backpressure/autoscaling).”

Timothy Lee

Screened

Senior Full-Stack Engineer specializing in AI platforms and scalable web systems

Live Oak, FL11y exp

“Built and shipped production agentic/LLM systems that could safely perform real customer and subscription operations, not just answer questions. Demonstrates unusually strong depth in agent orchestration, tool safety, evals, tracing, and backend workflow design across Node.js/TypeScript, Go, Redis, Postgres, Kafka, and GPT-4.”

Durgaprasad G

Screened

Mid-level AI/ML Engineer specializing in LLM infrastructure, RAG, and agentic systems

New York City, NY3y exp

“Stripe engineer who owned and unified multiple team RAG systems into a shared production platform used by 200+ internal operators, deployed on EKS with Kafka ingestion and hybrid retrieval. Drove measurable business outcomes including <400ms latency, ~35% inference cost reduction, ~25% accuracy lift via fine-tuning, and real-time auto-approval of 80%+ merchant compliance applications through strong observability and reliability patterns.”

“Unity/C# gameplay engineer who has shipped a modular, data-driven combat ability system with strong measurable outcomes (≈80% fewer GC allocations, 15–20% better frame times, 10–12% higher early retention). Also integrated an LLM-driven NPC dialogue/quest hint system with a C#/.NET backend, caching/guardrails, and telemetry-driven iteration, and shipped Photon PUN real-time 4-player co-op plus a shared codebase across Meta Quest VR and iOS/Android.”