Vetted AWS Lambda Professionals

Jeremiah Medina

Screened

Senior AI/ML Engineer specializing in LLMs, RAG, and cloud-native MLOps

Orlando, FL11y exp

“Built and owned a real-time clinical AI assistant at Andor Health, taking it from prototype through deployment, monitoring, and iterative improvement. Brings strong healthcare-focused GenAI experience across RAG, hybrid retrieval, LoRA fine-tuning, and production Python services, with measurable gains in accuracy, speed, and reliability.”

“Engineering leader (Director of Development) with hands-on cloud and product experience who builds business-aligned technology roadmaps and scales teams. Delivered an enterprise cloud-migration enabler at UHG by implementing AD authentication and Terraform-based IaC for custom VM images while meeting 90-day InfoSec patch/rotation requirements, and drove a 20% lift in user consumption/retention by designing an interactive branded media portal experience for Sunkist.”

“Player-coach engineering leader focused on AWS ML infrastructure and deep learning image delivery: provisioned EKS/Kubernetes for multi-node training and automated image release pipelines (Python + AWS CDK) to cut release time from 2 weeks to 1. Also built customer migration tooling for SageMaker HyperPod and owned a security incident end-to-end, implementing prevention tests and process improvements.”

Jared Wiener

Screened

Senior Solutions Architect & Full-Stack Developer specializing in Media & Entertainment on AWS

Santa Monica, CA20y exp

“Engineering/product leader with experience at ABC News and AWS who built newsroom collaboration and internal tooling initiatives into a full department, aligning roadmaps to business outcomes and navigating Disney-scale bureaucracy. Demonstrates hands-on architectural depth in serverless systems (Lambda/SQS/Parquet) and strong distributed-team operating cadence (Kanban/Asana, Jira/GitHub, Zoom/Slack), including leading while frequently traveling to evangelize and test products across bureaus.”

Rakshak Shah

Screened

Intern Software Engineer specializing in cloud, AI, and systems programming

Seattle, WA1y exp

“AWS intern who significantly evolved a Drift Audit Service backend (Control Tower/EventBridge context) to make drift findings more explainable and reduce false positives by adding a verification step in Lambda before event ingestion. Demonstrates strong API design fundamentals in Python/FastAPI (contracts, idempotency, security controls) and careful rollout practices (feature flags, canaries, phased deployments).”

Kaushik Sriram

Screened

Mid-level Software Engineer specializing in event-driven FinTech backend systems

San Francisco, CA5y exp

“Senior/Staff-level backend/platform engineer who owned Stripe’s global payout settlement system end-to-end, building an event-driven Python/Kafka platform processing millions of events daily across 30+ countries. Deep experience operating high-reliability distributed systems in production (incidents, replays/backfills, schema evolution, observability) and scaling on AWS/EKS with strong testing and deployment practices.”

“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.”

“Meta engineer who emphasizes AI-native development workflows, using Claude Code heavily to ship UI and performance fixes quickly. Notable examples include a location-aware ad relevance feature that increased CTR and revenue, and a vehicle insights chatbot whose UX improved through metric-driven prompt tuning.”

“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.”

“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.”

“AI/LLM engineer who built and productionized an internal RAG-based knowledge system that ingests diverse sources (PDFs, Markdown, Slack), scaled retrieval with distributed FAISS and parallel ingestion, and reduced hallucinations via re-ranking, grounding prompts, and post-generation validation. Also has hands-on orchestration experience with Airflow and Kubernetes for reliable ETL/model pipelines, monitoring, and staged rollouts; reports ~15% accuracy improvement and adoption as the primary internal knowledge tool.”

“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.”

Dhruv Arora

Screened

Senior Generative AI Implementation Consultant specializing in RAG and agentic AI on cloud

Bay Area, CA3y exp

“LLM/RAG practitioner who built an AWS-based enterprise document search and summarization platform with RBAC and scaled it to 10K+ users, solving relevance issues via contextual chunking and hybrid retrieval. Also designed agentic workflows for a telecom forecast-validation use case using sub-agents, tool APIs, and strict context management, and has proven pre-sales influence (supported a $300K manufacturing deal with a roadmap-driven pitch).”

PoHung Chen

Screened

Junior AI/ML Engineer specializing in MLOps and real-time model serving

New York, NY2y exp

“Software engineer with Amazon experience who has built LLM-powered and hybrid ML systems for ad auction/relevance at massive scale. Most notably, they described redesigning brand-query classification with a GPT-4-assisted offline cache plus fallback architecture that improved accuracy from 72% to 99%, reduced latency and costs, and was credited with an estimated $130M revenue lift.”

“Atlassian ML/AI engineer who has shipped end-to-end production systems combining classical ML, streaming infrastructure, and LLM-based personalization to improve onboarding and free-to-paid conversion. Particularly strong in turning research-style RAG and reranking ideas into low-latency, reliable product systems with robust evaluation, safety guardrails, and reusable platform services for other teams.”

“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.”

“ML/LLM engineer with Stripe and Adobe experience who productionized a transformer-based Payments Foundation Model for real-time fraud detection at global scale (billions of transactions). Built petabyte-scale ETL/feature pipelines (Spark/EMR, Airflow, dbt, Kafka/Flink) and achieved <100ms multi-region inference (EKS, TorchServe, edge/Lambda, GPU/CPU routing) with strong PCI-DSS/GDPR compliance and explainability (SHAP/LIME), reporting a 64% fraud accuracy improvement.”

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).”

“Built and owned the end-to-end architecture for a Quick Flows “research card” backend at AWS, using an event-driven AWS stack (SNS/SQS, DynamoDB, S3) to support asynchronous research output processing and status tracking. Emphasized maintainability via unit tests, smoke tests, and CI/CD with staged environments (devtest and gamma).”

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.”