Vetted MongoDB Professionals

“IAM/platform engineer with experience at DocuSign and Siemens who ships production-grade systems end-to-end: built a secure AWS serverless internal employee-profile API (OAuth2/Cognito/WAF) that cut data retrieval from weeks to near-instant and sustained ~2,800 RPS at ~75 ms. Also delivered production AI workflows, including a GPT-4o + Playwright crypto-scam detection agent and an NLP ticket-routing system improved to ~86.7% accuracy with strong monitoring and incident mitigation practices.”

“AI/ML engineer with experience spanning Accenture healthcare NLP systems, academic research, and Apple on-device LLM integration. Stands out for owning regulated production pipelines end-to-end—from HIPAA-compliant clinical NLP and EHR integrations to incident prevention, experiment tracking, and optimized on-device inference with LLaMA 3.”

“Engineer with experience at Reddit working on high-scale backend and infrastructure problems, including API redesign for products serving 150M+ daily active users. They also built a production AI agent for automated bug triage with 97% accuracy and substantial time savings, and have hands-on full-stack/AI side-project experience using React, TypeScript, Supabase, and LLMs.”

“Unity/C# gameplay engineer with strong systems architecture depth who has reworked core gameplay ability frameworks, shipped across mobile and standalone VR, and solved multiplayer synchronization issues with server-authoritative netcode. Also brings an unusual crossover into AI tooling, having owned an AI-powered debugging assistant at Arm and integrated LLM workflows into CI/development pipelines.”

“Engineer with startup experience at a Series B company, where they worked through high ambiguity and personally led an observers feature for a video conferencing platform. They also bring B2B SaaS experience building feature-flagged, permission-sensitive products for customers ranging from startups to large enterprises, plus migration experience moving an acquired app from .NET into a React/Next.js ecosystem.”

“Robotics software engineer with hands-on ROS2 experience building an audio conversion node and integrating Whisper LiveKit for streaming speech-to-text in a simulated hostile (outer space) robot environment. Also worked on a 2023 LiDAR + ML vision obstacle-detection project for a hospital-nurse-assistant robot, and has strong large-scale CI/CD deployment experience from AWS (2022–2024) across alpha/pre-prod/prod stages.”

“Built and deployed a healthcare NLP application that used an LLM-style physician interface feeding a random forest model to predict treatment plans for hard-to-triage patient subgroups, backed by a Databricks medallion pipeline and heavy feature engineering to address missing/low-integrity data across ~50K patients. Also delivered an earlier Microsoft AI Builder automation that improved transportation bill payment workflows by training non-technical payroll/procurement teams to use automated outstanding-payables reporting.”

“Engineering leader with experience building point-of-care diagnostics platforms (IoT-connected PCR device delivering results in <15 minutes) and scaling multidisciplinary teams (55+). Has led major data/IoT architecture decisions (multi-cluster Kubernetes with secure routing; Kafka + Gobblin over MQTT) and runs execution with Agile roadmaps tightly aligned to GTM and senior leadership.”

Zahaan Khan

Screened

Mid-Level Full-Stack Software Engineer specializing in ads transparency platforms

San Jose, USA6y exp

“TikTok engineer (4 years) who built and owned multiple ad transparency platforms used by internal teams and advertisers worldwide. Strong full-stack profile spanning Next.js/TypeScript + Redux frontends, a secure/optimized BFF layer, and event-driven backend workflows (Kafka, retries/DLQ, Redis idempotency) with heavy emphasis on observability and performance; cites a 20% moderation efficiency gain on a modernized legacy tool.”

“Software engineer who has deeply integrated AI into day-to-day development, using Claude Code, ChatGPT, and coding agents to speed up boilerplate generation, system design, and tradeoff analysis. Stands out for a pragmatic multi-model workflow focused on faster delivery and quicker architectural feedback.”

“Engineering leader who built and delivered an IoT smart-spaces platform for the self-storage and smart-living domains, translating customer requirements into architecture, capability maps, and a multi-milestone roadmap. Personally stood up missing AI/ML capabilities (including churn prediction) using Databricks (Delta Lake/MLflow), enabling follow-on features like energy optimization and security/anomaly detection. Scaled an org from 20 to 80+ with disciplined Agile planning (Jira Advanced Roadmaps/Confluence) and strong executive/customer-facing leadership during high-stakes customer commitments.”

Timothy Lee

Screened

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

Live Oak, FL12y 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.”

“Entrepreneurially driven technical leader seeking to partner with a founder/business plan owner to provide technical expertise. Helped drive Wiser's expansion into Europe by evaluating acquisition targets' technical estates and making the recommendation that was chosen. Applied lean, high-leverage product thinking at Nabis on a two-sided marketplace, delivering buyer value with a simple algorithm and later adding paid boosting for brands.”

“Graphics software engineer with academic robotics/HRI experience at Oregon State University under Dr. Heather Knight, leading a ROS+Python physical robot and Unity/C# VR system to study how motion/texture/collisions are perceived in VR (2 papers + thesis). Also built ROS-based Wizard-of-Oz TurtleBot study systems and multi-robot coordination experiments, plus industry experience with Docker/Kubeflow ML tooling and Azure DevOps CI/CD automation.”

“End-to-end product engineer who built and shipped Shopify Magic, an LLM-powered product-description generator on Amazon Bedrock with RAG over a tenant-isolated vector database, achieving 50% faster content creation, sub-2s latency, and 70%+ merchant adoption. Also led a Flexport migration from a monolithic Rails app to microservices using feature flags and parallel runs, delivering zero downtime and a 60% improvement in development speed.”

YAKKALI PAVAN

Screened

Mid-level Machine Learning & Generative AI Engineer specializing in NLP, CV, and RAG systems

USA6y exp

“Built and deployed a production LLM-powered RAG document intelligence system used by non-technical enterprise stakeholders, cutting document search time by 40%+ while improving answer consistency. Demonstrates strong MLOps/data workflow orchestration (Airflow, AWS Step Functions, managed schedulers across GCP/Azure) and a metrics-driven approach to reliability, evaluation, and cost/latency optimization with guardrails and observability.”

Bennett Smith

Screened

Senior Full-Stack Engineer specializing in cloud-native microservices and React

Los Angeles, CA14y exp

“Backend/data engineer with strong AWS production experience spanning high-traffic FastAPI APIs (Postgres/Redis/Kafka) and serverless+container deployments (Lambda/ECS) managed via Terraform and CI/CD. Has built Glue-based data lake ETL (S3 Parquet, Athena/Redshift) with schema drift/data quality controls, modernized legacy batch systems via parallel-run parity validation, and demonstrated measurable SQL performance wins (60–90s down to 3–5s).”

Elvis Rodriguez

Screened

Mid-Level Software Engineer specializing in Python, data pipelines, and FinTech systems

Remote3y exp

“Software/data engineer with experience at Google and on Bloomberg-related financial data modernization, building Python pipelines that convert legacy financial datasets into modern structures and iterating based on client feedback (e.g., adding historical change tracking for private placement data). Also built an internal Google usage-metrics dashboard pipeline using Protocol Buffers and scaled execution via sharded parallel cron jobs while scheduling off-hours to avoid impacting a testing tool.”

“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.”

“Data science/NLP practitioner with experience at NVIDIA and Microsoft building production-grade NLP and data-linking systems. Has delivered high-performing pipelines (e.g., F1 0.92) and large-scale entity resolution (F1 0.89), plus semantic search using embeddings and Pinecone with ~30–40% relevance gains, backed by rigorous validation (A/B tests, ROUGE, MRR) and strong MLOps/workflow tooling (Airflow, Databricks, FastAPI, MLflow, Prometheus/ELK).”

“ML/NLP engineer with experience building production-grade legal-tech and data platforms, including a GPT-4/LangChain contract review system using ElasticSearch embeddings (RAG) deployed on AWS EKS. Strong in entity resolution and scalable batch/streaming pipelines (Kafka/Spark), with measurable impact (70%+ reduction in contract review time) and a focus on monitoring and CI/CD for reliable delivery.”

“ML/robotics engineer with Apple experience who built a computer-vision-driven industrial defect detection system integrating a robotic arm with ROS-based real-time inference on an edge GPU. Drove major performance gains (cut inference time ~60% via quantization + TensorRT) and improved robustness to lighting/material variation, with strong emphasis on production reliability (health checks, watchdogs, observability, CI/CD) and interest in shaping early-stage startup engineering culture.”

Sandeep Rohilla

Screened

Principal Backend/Platform Engineer specializing in GenAI agent orchestration and LLM pipelines

San Francisco, CA19y exp

“LLM-focused engineer/sales-engineering profile with hands-on experience productionizing complex systems: scalable distributed architecture, multi-tenant monitoring, canary/shadow rollouts, and robust fallback strategies. Demonstrated real-time troubleshooting depth (p99 latency spikes traced to DB connection limits causing retry storms) and strong developer-facing communication via RAG workshops and live, customer-specific demos that helped close deals quickly.”

“Built and shipped production AI systems spanning customer support automation at Uber, privacy-preserving federated health modeling on iOS, and an open-source semantic search layer for Postgres. Stands out for combining strong LLM/product instincts with rigorous eval design, measurable production impact, and zero-to-one execution across backend, mobile, and developer infrastructure.”