Vetted Amazon DynamoDB Professionals

“Open-source JavaScript library contributor/maintainer focused on performance and usability—uses profiling and user feedback to optimize large-dataset processing and modernize abstractions. Refactored a nested-callback event handling system into an observer-pattern dispatcher with batched event queues, reducing CPU usage and improving maintainability; also handles community-reported crashes by reproducing issues, fixing memory leaks, and updating docs.”

“Hands-on backend/AI engineer who solo-built two production Claude-based agent systems: an internal Slack RAG over Confluence/Jira/code/regulatory docs and a HIPAA/GDPR-compliant patient chatbot with embedding guardrails and expert-in-the-loop evals. Also architected a multi-region patient portal + microservices platform with Terraform/CI-CD and federated gateways, delivering major onboarding automation and strong reliability wins (PgBouncer, chaos/perf testing).”

“Backend engineer with American Express experience maintaining an internal Python/Flask rewards simulation microservice used by product analysts and QA. Demonstrated strong performance and scalability work: moved batch simulations to Celery, added Redis caching to cut DynamoDB latency, and tuned Postgres/SQLAlchemy queries with EXPLAIN ANALYZE and composite indexes (bringing API responses under ~200ms by queueing jobs). Also has experience integrating ML via Flask-based model-serving APIs (scikit-learn/LightGBM packaged with joblib) and designing multi-tenant data isolation and tenant-specific configuration systems.”

“Backend/ML platform engineer in the insurance domain who built and shipped an AI-driven risk scoring/fraud detection service for underwriting. Runs containerized .NET Core and Python inference services on Azure (AKS + GPU nodes) with Terraform/ARM and Azure DevOps CI/CD, and has hands-on experience improving reliability under peak load plus implementing production AI guardrails (drift monitoring, fallbacks, human review, audit logs).”

“Data engineer focused on AWS-based enterprise data platforms, owning end-to-end pipelines from multi-source batch/stream ingestion (Glue/Kinesis/StreamSets/Airflow) through PySpark transformations into curated datasets for Redshift/Snowflake. Emphasizes production reliability with strong monitoring/observability and data quality gates, and reports ~30% performance improvement plus improved SLAs and latency after optimization.”

Apurva Banka

Screened

Mid-level Full-Stack & AI Engineer specializing in cloud, data platforms, and LLM automation

Houston, TX5y exp

“Software engineer/product builder who has owned an agentic affiliate lead-gen platform end-to-end (Django + React/TypeScript) and deployed it on Kubernetes in anticipation of 10x user growth from ~5K DAUs. Also has healthcare claims microservices experience using Kafka, including hands-on performance tuning to address consumer lag and broker pressure, and built an internal downtime alerting tool adopted across the organization.”

Vedang Jadhav

Screened

Mid-Level Software Engineer specializing in cloud-native microservices on AWS

New York City, NY5y exp

“Backend engineer with experience across healthcare and fintech platforms (Anthem, Citia) building high-throughput Python microservices with strong compliance/security focus (HIPAA, tenant isolation). Has integrated ML workflows into production systems (ResNet embedding-based image similarity) using async pipelines (Celery/Redis) and AWS (Lambda/S3/ECS), delivering measurable performance and fraud/content-integrity improvements at scale.”

Mike Gardiner

Screened

Technology Executive / Engineering Director specializing in AI-driven platform transformation

Lehi, UT12y exp

“Built a 0-to-1 iOS mobile gardening application that helps users plan, track, and harvest crops with pest control guidance, weather, and climate-zone-based planting date recommendations. Demonstrated strong customer discovery and MVP-first product execution, including a major data challenge: compiling US climate zone data for every ZIP code from widely dispersed public sources into an app-ready database.”

“Built a Python pipeline to monitor and classify public posts from sources like Hacker News and Reddit for SWE/tech job opportunities, with a strong focus on reliability, observability, and recoverable failures. Also currently building a court queueing system for the UCSD Badminton Club, showing an ability to turn messy, informal real-world processes into practical automation through iterative user feedback.”

“Healthcare AI engineer with hands-on ownership of production ML and LLM systems at McKesson, spanning clinical risk prediction and RAG-based documentation tools. Stands out for combining deep clinical-data experience, HIPAA-aware deployment practices, and measurable impact through reduced readmissions, clinician workflow gains, and 20% to 30% faster ML delivery for engineering teams.”

“Multi-time founding team member who helped raise capital at HotSchedules and Axial Shift, contributing investor-facing narratives around cost to serve, technology vision, scalability, and market opportunity. Motivated by building companies from the ground up, they bring a hands-on zero-to-one mindset paired with a strong understanding of what angels and VCs need to see in a scalable, standards-compliant product.”

Apoorv Bankey

Screened

Mid-level Backend Engineer specializing in distributed systems and FinTech

New York City, NY6y exp

“Engineer who uses AI and multi-agent workflows as a force multiplier while keeping architecture, security, scalability, and production quality under human control. Shared a concrete example of accelerating a backend-heavy SaaS email ingestion platform with authentication, role-based APIs, database models, and deployment setup using agent-style development and review.”

Harika M

Screened

Mid-level Full-Stack Developer specializing in FinTech and enterprise platforms

Plano, TX6y exp

“Engineer with a pragmatic, production-focused approach to AI-assisted development, using tools like Copilot and ChatGPT to accelerate coding while maintaining strict validation for correctness, security, and performance. Particularly notable for building a multi-agent incident-resolution workflow for a financial platform, with specialized agents for log analysis, root cause identification, fix suggestions, and test generation.”

“DevOps- and infrastructure-focused engineer who is already applying AI in practical delivery workflows, including Terraform, CI/CD, Kubernetes, and multi-agent automation. Stands out for combining AI-driven productivity with disciplined validation through testing, code review, and security checks, and for leading cross-functional AI integration across development, QA, and infrastructure.”

“Built an itinerary-planning startup MVP (LessGO) using React/TypeScript and a Node/Express backend integrating Google Maps and Gemini AI. Notably optimized Gemini latency from ~40 seconds to ~3 seconds through frontend caching, debugging, and model selection, and has TA experience supporting others with deployments and database connectivity.”

Aswin Jojo

Screened

Junior Software Engineer specializing in full-stack development and machine learning

Houston, TX3y exp

“Full-stack engineer with experience owning products end-to-end in both insurtech/financial workflows and AI-enabled IT operations. Built scalable React/Node and FastAPI systems, improved reliability under peak transaction load with SQS/Redis, and shipped an AI ticket-classification platform that cut response times from 3 days to 1 day.”

KUSHWANTH MUTHYALA

Screened

Senior Full-Stack Engineer specializing in FinTech

Irvine, CA6y exp

“Engineer with hands-on experience building and deploying end-to-end ML inference pipelines using SageMaker, TensorFlow, Scikit-learn, and Kafka-backed real-time data systems. Brings a strong distributed-systems mindset and has already operated in a tech lead capacity through architecture decisions, code reviews, and cross-functional coordination. Especially compelling for teams building production AI/ML platforms that need both practical execution and sound engineering judgment.”

Pallavi Hogalagere Anandareddy

Screened

Mid Software Engineer specializing in backend systems and FinTech

Tampa, FL4y exp

“Backend/full-stack engineer with experience spanning banking implementations at FIS and hands-on product building in React, TypeScript, Node.js, SQL, and Python. Stands out for owning six bank go-lives end-to-end, building an AI resume evaluator, and proactively automating manual operations workflows to reduce errors and improve consistency.”

“Backend-leaning full-stack engineer who has shipped both enterprise workflow software and AI-powered document intelligence products. Stands out for combining practical product judgment with strong production debugging skills across Spring Boot, GraphQL, FastAPI, vector search, and RAG systems, and for improving adoption by making AI search experiences intuitive for non-technical users.”

“New grad software engineer with hands-on experience building production full-stack analytics infrastructure during a Swiftwise AI internship and independently shipping AI products. Stands out for combining strong TypeScript/React/backend fundamentals with practical RAG and agent-building experience, including a poker coaching assistant built solo from ingestion and retrieval through prompt tuning and evaluation.”

“Full-stack engineer with hands-on ownership of a production telemedicine dashboard at Cleveland Clinic, spanning React/TypeScript frontend, Spring Boot and Node.js backend services, and AWS/Kubernetes infrastructure. Stands out for real-time systems expertise, measurable performance improvements in a healthcare setting, and a clear interest in applying that backend/cloud foundation to AI agent systems.”

“Founder of Snazified Inc., a multi-tenant ATS startup, where they led a 5-person remote engineering team and built AI-powered workflow features that reportedly drove 75% sales growth and 90%+ customer retention. They also launched a separate subscription profile platform with React/Node, AI resume tools, and job aggregation, reaching 50 paying subscribers shortly after launch.”

Alex Guzman

Screened

Principal Software Engineer specializing in cloud infrastructure and identity systems

Denver, CO17y exp

“Senior backend-leaning engineer with experience spanning an 8-person early-stage startup and production microservices environments. They helped deliver an MVP for a fintech/charitable donations product by building a resilient abstraction API across multiple rewards vendors, and more recently maintained Go services at scale with Kubernetes autoscaling for workloads reaching roughly 1 million requests per day.”

“Full-stack engineer who shipped a production "Financial Insight" assistant dashboard in Next.js App Router/TypeScript, integrating a RAG pipeline (embeddings + ChromaDB + LLM) via route handlers and owning post-launch performance (latency, token cost, retrieval relevance). Also built/optimized Postgres-backed workflows for an outbound dialer and callback routing engine handling ~10,000 daily contacts, validating query performance with EXPLAIN (ANALYZE, BUFFERS).”