Vetted Amazon S3 Professionals

Rojin Bakhti

Screened

Junior Software Engineer specializing in Edge AI and ML deployment

San Diego, CA3y exp

“Qualcomm engineer building Android applications that run on Qualcomm AI accelerators, with hands-on experience in C++ concurrency, chipset stress testing, and power/performance tuning. Has deployed on-device AI models and built deployment/log post-processing workflows using Docker/Kubernetes and CI/CD; interested in translating this embedded AI/performance background into robotics (perception/real-time systems).”

Hitesh Bhojwani

Screened

Mid-level Robotics Software Engineer specializing in SLAM and 3D computer vision

4y exp

“Robotics software engineer focused on outdoor mobile robot localization and navigation, building ROS1/ROS2 systems with NavSat+EKF sensor fusion and custom Nav2/Costmap2D extensions for 3D obstacle clearance. Demonstrates strong real-world troubleshooting by tracing localization drift to a failing IMU connector, repairing it, and then creating sensor-health monitoring tooling; experienced taking features from Gazebo simulation through field testing to Docker/Kubernetes deployment with CI via GitHub Actions.”

“Backend-focused engineer who uses AI pragmatically as a force multiplier rather than a substitute for engineering judgment. They stand out for applying structured, agent-style workflows to code generation, debugging, and production log analysis while maintaining strong emphasis on correctness, performance, and reliability in backend and microservices environments.”

“Built and architected ML-integrated payment processing systems for PlayStation at Sony Interactive Entertainment, covering fraud determination, provider routing optimization, and model-training feedback loops in production. Brings a strong reliability and observability mindset, with concrete experience designing fallbacks, retries, correlation-ID tracing, and statistically grounded evaluation for non-deterministic systems.”

“Software engineer at Paradigm who is deeply hands-on with agentic development workflows and AI-assisted coding. He built an in-house OAuth layer to replace a third-party service and reduce projected integration costs, and also created an "ambient agent" that proactively responds to user behavior on the website. He stands out for combining full-stack architecture thinking with a disciplined, model-aware workflow for designing, implementing, and reviewing AI-generated code.”

“Staff-level engineer with a track record of building greenfield, high-impact platforms inside major enterprises like Apple TV, CAA, and Disney. Particularly compelling for teams that need startup-style ownership with enterprise-grade execution: they’ve driven cross-department adoption, built AI and real-time systems hands-on, and delivered measurable operational gains in media, content, and ERP environments.”

“Data engineer/backend developer with experience owning end-to-end, high-volume data pipelines for ML/analytics using Python, Airflow, SQL, and PySpark, reporting ~30% error reduction through improved reliability and data quality checks. Has also built Django-based REST APIs with caching/pagination and strong versioning practices, and operated external data collection/web scraping pipelines with anti-bot measures, monitoring, retries, and idempotent backfills.”

“Full-stack engineer with strong AI systems and B2B SaaS experience across BrightOps, Zapier, Nordstrom, and Calendly. They’ve owned architecture for an AI-powered tutoring platform, improved retrieval quality with a hybrid vector-plus-keyword approach, and built Go services processing over 1 million student events per day. Particularly compelling for teams building data-intensive, reliability-critical products with LLM, workflow automation, or compliance-oriented use cases.”

“Built and shipped customer-facing AI systems in banking, including an AI fraud support workflow and virtual assistant at Citi/Citibank that handled over 1 million conversations per month. Combines full-stack engineering, LLM/RAG architecture, and strong compliance-minded design with PII masking, audit logging, confidence thresholds, and human escalation for regulated environments.”

“Backend/data engineer with production experience building credit/fraud enrichment services and checkout pipelines on AWS (EKS + Lambda) using FastAPI, Kafka, Postgres, and Redis, with a strong focus on reliability patterns (timeouts/retries/circuit breakers) and observability. Has also built AWS Glue/PySpark ETL into S3/Redshift with schema evolution and data quality controls, and modernized legacy credit decisioning into Java/Node microservices with parallel-run parity validation and feature-flag rollouts.”

“Robotics/computer-vision engineer with industrial safety monitoring experience, building real-time pose estimation (TRTPose) and 2D-to-3D localization and optimizing pipelines to sustain 30+ FPS under heavy multi-entity load. Also brings edge-to-cloud distributed systems work (HoloLens + Google Vision/Translation) and production ML deployment experience using Docker/CI/CD across finance and edge camera environments.”

“Engineering leader who managed a 20-person cross-functional team building customer-driven software solutions, delivering a 50% reduction in simulation/test lifecycle and securing a long-term strategic SLA. Strong in scalable data ingestion architectures (FastAPI + Kafka + multiprocess workers), operational diagnostics (correlation IDs/centralized logging), and microservice decoupling for analytics/visualization. Active open-source contributor who shipped a NATS bug fix and improved SDK onboarding with automation that cut ramp time by 30%.”

“Technology leader with experience owning enterprise roadmaps and executing large-scale platform standardization during rapid M&A—most notably driving a tech roadmap across a 37-company portfolio at Regent, tackling technical debt and security gaps via unified cloud-native architecture, IAM/logging, CI/CD, and a global SRE model. Previously scaled an Adobe engineering org from 8 to 40+ across four regions, implementing clear org design, KPIs, and an extreme-ownership culture to support 24/7 operations and enterprise needs.”

“Backend-focused engineer with hands-on experience modernizing a legacy SNMP/PNM data collection system at CableLabs into a cloud-accessible Kubernetes pipeline, feeding Prometheus-formatted metrics into VictoriaMetrics and visualizing real-time network health in Grafana for 100+ modems. Also built a FastAPI + Supabase appointment booking portal for a clinic with encryption and phone-number-based auth, and has frontend experience debugging S3-based HEIF image rendering issues.”

“Financial systems engineer who built an automated rebalance-day order reporting and analytics tool on kdb+ pipelines, cutting a high-visibility manual process from 2–3 hours to ~2 minutes and expanding it from North America to EMEA/APAC. Also proposed an early production RAG-based incident knowledge assistant trained on ServiceNow postmortems, with guardrails to scope retrieval by application.”

Matthew Frank

Screened

Senior Machine Learning Engineer specializing in computer vision and LLM-powered analytics

Santa Barbara, CA7y exp

“Machine learning engineer and startup veteran building InfraSketch (infrasketch.net), a full-stack system-design/diagramming product where users describe systems in plain English and an LLM agent generates and iterates on infrastructure graphs and exports design docs. Owns the entire stack (React/TS + FastAPI/Node, DynamoDB/Postgres, AWS serverless) and focuses on LLM consistency, modular agent architecture, and production-style CI/CD and reliability patterns.”

Vindhya Naidu

Screened

Mid-level Backend Software Engineer specializing in Java/Spring microservices and FinTech

Austin, TX5y exp

“Backend engineer with Apple experience who owned production platform improvements end-to-end, including a Redis caching layer that cut API latency ~35–40% and reduced DB load. Has hands-on on-call/incident response and observability (CloudWatch), plus experience scaling Docker/Kubernetes microservices and operating Kafka-based telemetry pipelines with schema evolution, deduplication, and replay/backfill handling.”

“Primary engineer at Customer Insights AI who built an end-to-end Python pipeline for 340B drug pricing compliance, using ML to detect suspicious pharmaceutical claims and benefit diversion. Stands out for combining healthcare compliance domain knowledge with production reliability practices, and for turning ambiguous analyst-driven review processes into automated workflows that cut manual review by 70%.”

“ML/GenAI engineer with hands-on experience shipping LLM-powered support systems at Uber, including real-time feedback analysis, ticket summarization, and retrieval-grounded knowledge systems. Stands out for combining fine-tuning, RAG, safety evaluation, and production optimization to drive measurable support outcomes like faster handling times, better resolution rates, and lower latency/cost.”

Jiajun Huo

Screened

Mid-level Software Engineer specializing in AI, data infrastructure, and LLM systems

Urbana, IL4y exp

“Built end-to-end data and automation systems at Sonic SVM, spanning Python/FastAPI/Kafka/Spark ingestion pipelines, warehouse analytics, and Playwright automation for brittle SSO-protected dashboards. Stands out for combining backend/data engineering with strong observability and reliability practices, plus a pragmatic ability to turn messy manual business processes into measurable self-serve workflows.”

Christopher Kirby

Screened

Executive engineering leader specializing in platform engineering, AI systems, and SaaS

Detroit, MI24y exp

“Senior engineering executive who has repeatedly rebuilt and scaled product engineering organizations in high-growth environments, including restarting Rocket Auto’s stack from scratch and hiring 100+ engineers during StockX’s hypergrowth phase. Particularly differentiated by being unusually hands-on for an executive leader, with active open source work and a strong focus on AI-native engineering workflows, developer automation, and modern architecture transformation.”

“Full-stack product engineer with deep JavaScript/TypeScript expertise who has led backend architecture for FanDuel's sportsbook platform and shipped high-scale systems serving roughly 400 million requests per day. Combines React/React Native product delivery with strong performance and resiliency engineering, including major latency gains, CDN/cache improvements, and features used by millions at both FanDuel and Max.”