Vetted REST API Professionals

Aaditya Voruganti

Screened ReferencesStrong rec.

Junior AI & Software Engineer specializing in robotics and ML infrastructure

2y exp

“Robotics engineer from UIUC’s Intelligent Motion Lab who led the perception stack for a humanoid robotic nurse, fusing camera/LiDAR/IMU on NVIDIA Jetson Orin for real-time localization and scene understanding across six robots. Deep expertise in ROS 2 and edge ML optimization (TensorRT, CUDA, zero-copy), delivering major latency/throughput gains (10 FPS to 22+ FPS) and building fault-tolerant pipelines with gRPC offloading and real-time reliability practices.”

“Healthcare solutions architect with roughly 7 years at Mass General Brigham, evolving from application specialist to broad cross-functional architect supporting telehealth, digital health, conversational AI, generative AI, and legal workflow initiatives. Particularly strong at translating complex clinical and business problems into enterprise architectures, integrations, and stakeholder-specific demos across hospital leadership, clinicians, IT, and vendors.”

“Senior engineering/CTO-level leader with hands-on delivery of serverless, event-driven cloud governance platforms (deployed across multiple GE business units) and experience building adaptable usage-based billing at UserTesting. Has advised startups (including CaseText during YC) and supported fundraising and acquisition due diligence, including investor materials for a smart cooler custody management system presented to BARDA during Operation Warp Speed.”

“Backend engineer who evolved the X-Ray gaming analytics platform, leading a zero-downtime MongoDB→AWS DocumentDB migration with dual-write, checksum-based validation, and Kubernetes canary rollouts while maintaining real-time monitoring for millions of concurrent sessions. Strong in FastAPI/Python API scaling and performance tuning (cut latency from ~2s to <150ms and reduced DB load 90%) plus production-grade auth/RLS security patterns (JWT, Supabase Auth, PostgreSQL RLS).”

“Unity/C# gameplay engineer who has shipped both core systems and live multiplayer features, including a modular real-time inventory system that cut crashes by 80% and improved retention. Built an LLM-driven NPC dialogue pipeline with caching, fallbacks, batching, and fine-tuned models, iterating via player feedback and analytics. Shipped a Photon Fusion multiplayer metaverse with rigorous network simulation and CI stress testing, and has VR optimization experience (Meta Quest constraints) on Horizon Worlds.”

Surya Teja

Screened

Mid-level Backend/Full-Stack Engineer specializing in AI and FinTech payments

Tempe, AZ4y exp

“Full-stack engineer who has owned an operational reporting/dashboard product end-to-end—building a React UI, designing/implementing FastAPI services, and deploying/operating on AWS. Demonstrates strong performance engineering (Postgres query/index tuning using EXPLAIN ANALYZE) with concrete impact (reports reduced from tens of seconds to a few seconds) and a reliability mindset across observability, migrations, and resilient third-party/ETL integrations.”

Paul Liu

Screened

Senior Software Engineer specializing in cloud-native backend and web/mobile apps

Seattle, WA8y exp

“Backend engineer with Tesla experience building Python-based, serverless microservices for a supply chain portal, including a MongoDB-backed tracking/logging system and a reconciler Lambda to manage retries and failures. Has hands-on Kubernetes (EKS) and GitOps (Argo CD) experience, plus real-time Kafka pipelines for fleet/IoT telemetry and proxy-based migrations from monolith systems to AWS databases.”

Sourabh Jain

Screened

Director of Software Engineering specializing in enterprise Data, ML & AI platforms

Bay Area, CA23y exp

“Former Walmart Director of Software Engineering who left in March 2025 to build products for clients. Recently delivered an LLM/RAG-based UNSPSC classification solution for an MRO client using a multi-stage retrieval + web search + prompt-engineering workflow, and has led large-scale retail forecasting initiatives and high-severity cloud-migration incidents end-to-end.”

“Engineer with hands-on experience across backend, full-stack, cloud, and AI/ML systems, with particular depth in Python, FastAPI, AWS Bedrock, SageMaker, and RAG-based architectures. Stands out for treating AI and agents as accelerators within disciplined production engineering, emphasizing guardrails, observability, latency/cost monitoring, and scalable system design.”

“Frontend tech lead at HubSpot who shipped an LLM-powered insights dashboard that analyzed complex customer interaction histories and surfaced sentiment, challenges, and next-best actions for sales users. Stands out for having taken an AI feature beyond prototype into beta and full production, with strong emphasis on testing, maintainability, and practical production tradeoffs.”

“Candidate has developed a disciplined AI-first engineering workflow that combines design docs, prior PR analysis, testing plans, and multi-agent coordination to accelerate delivery without sacrificing quality. They described acting as a tech lead for AI agents, overseeing code structure, business logic, testing, and service contracts, and reported reducing manual coding effort by nearly 80%.”

“Full-stack builder with hands-on experience shipping both location-based consumer products and AI-driven data platforms. Has owned end-to-end systems across React/Next.js, FastAPI, PostgreSQL, Streamlit, and geospatial tooling, with a strong emphasis on modular architecture, LLM reliability, and turning messy real-world data into usable product experiences.”

“Full-stack engineer with a strong mix of real-time product engineering and applied AI experience. Built and deployed a production stock trading simulator on AWS and an LLM-based customer support agent with RAG/tooling, and also shipped a zero-to-one in-store detection feature at Meituan that improved CTR by 7% and conversion by 11%.”

“Full-stack AI engineer who has built both document-intelligence products and agentic investigation systems end to end. At ControlRooms.AI, they helped ship a production-facing root cause investigation workflow for industrial operations using Neo4j, FastMCP, RAG, OCR/VLM inputs, and multiple LLMs, contributing to roughly a 10x reduction in manual investigation time. They stand out for designing explainable, traceable AI systems that surface evidence, uncertainty, and missing context rather than forcing overconfident answers.”

“Full-stack engineer with startup-style experience building assessment and learning platforms using React, Node.js, Python, MongoDB, and PostgreSQL. Stands out for owning backend auto-grading and analytics features end to end, including concurrency-safe submission processing and database performance optimization for growing datasets.”

“Full-stack/backend-leaning engineer who has built internal operational dashboards and AI assistants, including a real-time dashboard used by engineering, operations, and management teams at NVIDIA. Brings a mix of Spring Boot, Angular/TypeScript, distributed-system performance tuning, and practical LLM integration with grounding, validation, and production monitoring.”

Jenya Rusinova

Screened

Mid-level Frontend Engineer specializing in cloud enterprise applications

East Palo Alto, CA3y exp

“Frontend-focused product engineer with experience owning production launches in observability/monitoring, including extending an existing web-only service to support mobile users without disrupting current customers. Stands out for balancing speed and safety through feature flags, regional beta rollouts, bug bashes, and close collaboration with PM, design, and backend teams in ambiguous environments.”

“Backend/data engineering candidate with Netflix experience designing and migrating analytics platforms from batch to real-time streaming (Kafka/Flink) across AWS and GCP. Delivered measurable improvements (40% lower data delay, 99.9% accuracy) using phased rollouts, automated data validation (Great Expectations), and strong observability (Prometheus/Grafana), and proactively hardened pipelines with idempotency to prevent duplicate Kafka processing.”

“Backend/data engineer with production experience building FastAPI services with strong reliability patterns (circuit breaker, rate limiting, caching, graceful degradation) and JWT/OAuth2 auth. Has delivered AWS EKS deployments via Terraform with Secrets Manager/IRSA and HPA autoscaling, and built Glue/Spark ETL pipelines on S3 Parquet with schema-evolution and idempotent reruns; also demonstrated measurable SQL tuning impact (20–30s to <10s).”

“Backend/distributed-systems engineer with Uber experience building real-time telemetry and safety signal pipelines. Strong in Kafka-based event-driven architectures, low-latency processing under peak load, and production reliability via monitoring, retries, and fallback logic; has Docker/Kubernetes and CI/CD deployment experience.”

“Full-stack engineer with deep serverless AWS experience who built VidToNote, an AI video analysis platform, end-to-end using Next.js App Router/TypeScript and an event-driven pipeline (API Gateway, Lambda, DynamoDB, S3, Step Functions, SQS). Strong on production reliability and observability (CloudWatch, X-Ray, structured logging), plus data/analytics work in Postgres with measurable query optimizations and durable LLM evaluation workflows. Amazon background; integrated 22 AWS services and completed AWS Solutions Architect Professional certification within a month.”

“Full-stack engineer in the investment tracking/financial reporting space who built an automated reporting dashboard and compliance/reporting pipeline end-to-end using Next.js (App Router, server/client components), REST, and Postgres. Demonstrated measurable performance wins (~30% faster loads) through caching and query optimization, and built durable orchestrated workflows in n8n with retries, idempotency, and reconciliation checks.”