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Vetted AWS Lambda Professionals
Pre-screened and vetted.
Jolie Qiu
Mid-Level Software Engineer specializing in AWS data infrastructure and pipeline automation
“AWS-focused software engineer who built a self-serve ETL pipeline scheduling service for non-engineers, including automated CloudFormation-based onboarding that cut setup time from 2–3 weeks to ~5 minutes. Strong in production reliability and customer-facing data platforms (EMR/DynamoDB/Lambda), with examples spanning pagination at scale, cross-table consistency, and phased rollouts to improve Parquet log SLAs.”
Arun Ganesh
Junior Software Engineer specializing in healthcare AI and cloud infrastructure
“Amazon Health AI engineer who has owned both full-stack clinical product features and production LLM systems end to end. Built HIPAA-compliant GraphQL and agentic RAG architectures for provider workflows across 125,000+ patients, with measurable impact including 30% higher clinical relevance, 55% lower lookup time, and 12% less false medical information.”
Nishitha Thummala
Mid-level AI/ML Engineer specializing in LLMs, RAG, and scalable inference
“Backend/retrieval-focused engineer with production experience at Perplexity building a large-scale real-time Q&A system using retrieval-augmented generation, emphasizing low-latency, high-quality answers through ranking, context optimization, and caching. Also has orchestration experience from both product-facing LLM pipelines and large-scale infrastructure workflows at Meta, and has partnered with non-technical stakeholders to align AI trade-offs with business goals.”
Kowshika M
Mid-level AI/ML Engineer specializing in LLM fine-tuning, inference optimization, and AI safety
“AI/LLM engineer with production experience at NVIDIA, where they fine-tuned and deployed a financial-services chatbot and cut latency ~50% using TensorRT + NVIDIA Triton, scaling via Docker/Kubernetes. Also has consulting experience at Accenture delivering a predictive maintenance solution for a logistics network, bridging non-technical stakeholders with actionable dashboards.”
Aravind Sudha
Director-level engineering leader specializing in cloud platforms and distributed systems
“Senior engineering leader at AWS currently managing two services in the MSK organization, including Replicator for disaster recovery/data distribution and Glue Schema Registry. He combines hands-on distributed systems depth with large-scale people leadership, having managed teams up to 32 engineers and coordinated platform onboarding work across roughly 340 AWS services. Earlier experience in payroll and compliance platforms adds strong enterprise domain breadth beyond cloud infrastructure.”
Dilpreet Singh
Executive CTO and Founder specializing in AI platforms and hyper-scale SaaS
“CTO-minded builder seeking to join a startup; previously created an AI-driven platform that abstracted away DevOps and infrastructure for drug discovery researchers. Emphasizes high-leverage, zero-to-one execution with managed cloud/open-source tooling, and a strong reliability/reproducibility mindset validated against existing scientific pipelines.”
“Backend/full-stack engineer (Amazon experience) who built an AWS-based integration testing platform using Flask, ECS, Docker, and CloudWatch—cutting 1000+ test cases from ~5 hours to ~30 minutes while improving log visibility for non-engineering users. Also led a zero-downtime EU region migration with rigorous ORR testing, and built a Kinesis/Firehose/S3 + Glue/Spark replay mechanism for resilient data recovery. Side project: reproducible, cost-efficient LLM hosting platform on EKS using CDK and Karpenter for scale-to-zero.”
Nikhil Reddy
Mid-level AI/ML Engineer specializing in GPU inference and LLM platforms
“Built and deployed an LLM-powered platform that turns models into scalable REST/gRPC APIs, focusing on keeping GPU-backed inference fast and stable during traffic spikes. Experienced with AWS orchestration (EKS/ECS/Step Functions), safe model rollouts, and production-grade monitoring/testing for reliable AI agents and workflows.”
Krishna Reddy
Mid-level AI/ML Engineer specializing in fraud detection and clinical LLM assistants
“Built and deployed a production clinical support LLM assistant at Mayo Clinic using a LangChain-orchestrated RAG architecture (Llama 2/PaLM) over de-identified clinical records, integrating BigQuery with Pinecone for semantic retrieval. Focused on healthcare-critical reliability by reducing hallucinations through grounding, implementing HIPAA-aligned privacy controls (Cloud DLP, VPC Service Controls), and running structured evaluations with clinician feedback.”
Dexin Huang
Junior AI Engineer specializing in LLM systems, RAG, and full-stack automation
“Built and deployed an AI receptionist product for field-service businesses (HVAC/electrician), including real-time Jobber scheduling integrations and Twilio-based calling. Combines hands-on customer/operator shadowing with strong production engineering (queueing to handle API limits, rigorous testing/mocking, mirrored prod environment) and cross-layer troubleshooting, driving user adoption through review/override workflows.”
Shilong Li
Intern Software Engineer specializing in backend and distributed systems
“Backend engineer with experience at ByteDance (TikTok monetization) and Baidu, plus a personal real-time course booking/tracking platform built with FastAPI, Postgres, and Redis. Demonstrates strong concurrency and reliability engineering (Redis distributed locks with TTL extension, idempotent event processing) and practical DevOps skills (Kubernetes/Helm, GitLab CI/CD, Docker build-time optimization).”
Pranav Hariharane
Mid-Level Backend Engineer specializing in REST APIs and AWS
“Backend engineer who built a new REST eligibility service at Barclays that unified siloed account logic (card/loan/deposit) and integrated with web/mobile, ultimately serving millions of users daily. Also built an end-to-end LLM-based pharmaceutical care-plan generation tool in a rapid Columbia startup competition, emphasizing configurable design, strict validation, persistence, and robust error handling.”
Kunj Amrutbhai Patel
Mid-level Software Engineer specializing in distributed backend systems on AWS
“Built production systems in the AWS ecosystem, including an internal AI assistant for diagnosing account transfer and permissions issues and an end-to-end account transfer workflow used by enterprise customers. Stands out for combining LLM/RAG design with strong distributed systems reliability practices, emphasizing guardrails, fallbacks, and operational trust in high-stakes workflows.”
MARCUS JOHNSON
Senior AI/ML Engineer specializing in Generative AI, NLP, and RAG systems
“ML/NLP engineer focused on production-grade data and search/recommendation systems: built an end-to-end pipeline that connects unstructured customer feedback with product data using TF-IDF/BERT, Spark, and AWS (SageMaker/S3), orchestrated with Airflow and monitored for drift. Also has hands-on experience with entity resolution at scale and improving search relevance via BERT embeddings, FAISS vector search, and domain fine-tuning validated with precision@k and A/B testing.”
Sai Gundeti
Mid-Level Backend Software Engineer specializing in distributed systems and billing platforms
“Full-stack engineer with Uber experience building finance/billing reconciliation systems: shipped and owned an internal operations dashboard (Next.js App Router/TypeScript) that cut investigation time from hours to minutes and improved load time from ~6–7s to <2s. Deep in Postgres modeling and performance (sub-200ms optimized queries) plus durable event-driven workflow orchestration with idempotency, retries/backoff, DLQs, and reconciliation jobs; also has seed-to-Series C startup experience emphasizing end-to-end ownership.”
Thuc Duong
Senior Data Engineer specializing in AI-driven GTM analytics and LLM evaluation
“Data/analytics engineer who stood up foundational pipelines and services at Meta for the Ray-Ban Meta launch—building a retailer sales ingestion system (S3/Hive) with rigorous DQ checks, 1-day SLAs, and dimensional rollups used by GTM to track sales trends. Also built a modular multi-retailer web-scraping system for out-of-stock alerts and shipped internal GraphQL APIs and an n8n-like workflow builder using serverless (AWS Lambda) with strong testing and observability practices.”
Aniket Singhal
Senior Software Engineer specializing in AWS-based distributed systems and FinTech platforms
“Backend engineer with Amazon experience building large-scale, automated financial/accounting and pricing systems on AWS. Designed a fault-tolerant Step Functions + DynamoDB workflow platform handling 100K+ messages/sec to compute fair values and generate journal entries in under 3 seconds, and led safe API refactors using shadow mismatch testing. Also uncovered a major legacy pricing bug (tax vs non-tax swap) that cut mismatch rates from 5–10% to ~0.5% and materially improved price acceptance/business outcomes.”
Michael Kaufman
Mid-Level Full-Stack Software Engineer specializing in mobile and web platforms
“iOS-focused engineer who led feature development for Amazon Books/Kindle (e.g., Series & Story So Far recaps, Kindle Memories) and introduced pure Swift packages while building sync and content download systems. Also has full-stack experience (React/TypeScript + Node with REST/GraphQL) and strong AWS operations (CDK/CI-CD, CloudWatch, canaries, autoscaling), plus founder experience at GLXY.ai shipping an early hardware MVP (weight sensors) under tight constraints.”
kartik kanotra
Mid-level Software Developer specializing in cloud data engineering and MLOps
“Software engineer with strong AWS production experience, including an end-to-end historical backfill system exporting ~10PB of CloudWatch logs into a data lake using Step Functions/Kinesis/Lambda/Firehose/Glue. Emphasizes reliability and operability (DynamoDB checkpointing, monitoring dashboards, CI/CD with canary tests) and has also built customer-facing UI work for the Visa Developer Portal using Angular + Spring Boot, plus React/Redux frontend work.”
Jim Glassman
Executive Technology Leader specializing in Enterprise AI, Cloud Architecture, and Data Platforms
“Senior data/technology executive who stays hands-on: currently building a Go micro-kernel orchestration layer for medical AI agents to boost concurrency and enforce HIPAA/PHI controls, achieving 26x throughput on migrated workloads. Has led large-scale transformations across healthcare and financial services, including a 45-day data warehouse rebuild at Elara Caring and a data/ML roadmap at Acelity credited with $230M in annual revenue impact prior to 3M acquisition.”
Senior Full-Stack Python Developer specializing in cloud-native RAG and microservices
Intern Software Engineer specializing in data science and network visualization
Mid-level AI/ML Engineer specializing in NLP, computer vision, and MLOps
Mid-level AI/ML Engineer specializing in recommender systems, fraud detection, and LLMs