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Vetted AWS Lambda Professionals

Pre-screened and vetted.

AZ

Anna Zhou

Screened

Mid-level Backend Software Engineer specializing in Go, AWS, Kafka, and DevOps

Seattle, WA5y exp
NordstromUniversity of Washington

Checkout-focused engineer with hands-on experience integrating many dependent microservices and Kafka event flows, including managing SLA/timeout issues with partner teams. Led a PayPal Braintree SDK migration across iOS/Android/web with strong testing discipline, and built an AWS Lambda automation to clean up stale CloudFormation test stacks to reduce monthly AWS spend.

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JK

Mid-level AI/ML Engineer specializing in conversational AI, NLP, and LLM-powered RAG systems

Jersey City, NJ5y exp
JPMorgan ChaseSaint Peter's University
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MS

Senior Machine Learning Engineer specializing in MLOps and Generative AI

St. Louis, Missouri7y exp
Emerson
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VR

Mid-Level Software Engineer specializing in Java/Spring Boot microservices and cloud DevOps

NJ, USA5y exp
Goldman SachsStevens Institute of Technology
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PK

Senior Data Engineer specializing in multi-cloud data platforms and generative AI

Weston, FL5y exp
UKGUniversity of Alabama at Birmingham
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TL

Senior Software Engineer specializing in ML/AI and scalable data platforms

San Jose, CA11y exp
LabelboxNational University of Singapore
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JF

Mid-level AI/ML Software Engineer specializing in Generative AI and NLP

Remote5y exp
EmerjenceBoston University
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SA

Sharath Addepalli

Screened ReferencesStrong rec.

Mid-Level Software Engineer specializing in Python microservices and scalable web APIs

Franklin, TN3y exp
NissanUniversity of Florida

Backend engineer who replaced an Excel-heavy forecasting workflow with a secure, auditable FastAPI system (React UI + relational model + async workers), emphasizing deterministic processing, idempotency, and versioned ledger-style ingestion. Led a monolith-to-FastAPI migration at Bounteous using a strangler approach, feature-flagged incremental rollout, and data reconciliation/shadow-compare to protect integrity while scaling onboarding workflows.

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RG

Rithindatta Gundu

Screened ReferencesStrong rec.

Mid-level AI/ML Engineer specializing in LLM systems and cloud MLOps

San Francisco, CA4y exp
Wells FargoSeattle University

Built a production LLM-powered fraud detection platform at Wells Fargo, combining OpenAI/Hugging Face models with RAG-based explanations to make flagged transactions interpretable for risk and compliance teams. Delivered low-latency, real-time inference at high scale on AWS (SageMaker + EKS), with strong observability and security controls, reducing manual reviews and false positives in a regulated environment.

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LD

Lavrenti DeLavrenti

Screened ReferencesStrong rec.

Director-level Technology Leader specializing in cloud-native platforms, AI/ML, and SaaS

Remote15y exp
Alioni Tech LabsGeorgian Technical University

Engineering leader (Director/VP level) who has repeatedly aligned product and engineering through ROI-driven quarterly roadmaps and strong stakeholder communication, including board presentations. Built a parallel cloud team to migrate an on-prem product to the cloud, credited with delivering $9M ARR, and led a Python monolith-to-serverless event-driven microservices transformation. Currently manages distributed teams across Mexico, India, and the US using pod-based structures, clear KPIs, and a supportive accountability culture.

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LV

Mid-level Software Engineer specializing in SRE, observability, and LLM-powered automation

Richardson, TX2y exp
CiscoWestcliff University
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NG

Naga Gayatri Bandaru

Screened ReferencesModerate rec.

Mid-level AI/ML Engineer specializing in MLOps and production ML systems

Cleveland, Ohio3y exp
Cleveland ClinicSan José State University

Backend/ML engineer who has shipped high-scale real-time systems across e-commerce and healthcare: built a PharmEasy real-time recommendation engine for ~2M monthly users (cut feature latency 5 min→30 sec; +15% cross-sell) and architected a HIPAA-compliant multimodal clinical diagnostic workflow (DICOM+EHR) with XAI, MLOps (MLflow/Airflow/K8s), and drift/monitoring guardrails supporting 10k+ daily predictions.

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MP

Manasa Pantra

Screened ReferencesStrong rec.

Junior Software Engineer specializing in AI, LLM systems, and full-stack development

Stony Brook, NY2y exp
Stony Brook UniversityStony Brook University

Product-focused full-stack engineer at startup (Zippy) who shipped a production multi-agent AI system for restaurant operations plus payments workflows. Built end-to-end: RAG grounded on a Notion knowledge base, structured function-calling task routing, FastAPI/JWT multi-tenant backend, and a polished React+TypeScript owner dashboard. Has real production incident experience (duplicate Stripe webhooks) and reports ~94% task-routing accuracy under load.

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UG

Utkarsh Gogna

Screened

Mid-level Full-Stack Software Engineer specializing in Java microservices and cloud-native systems

Boston, MA5y exp
CGINortheastern University

Backend engineer with experience building and modernizing high-volume healthcare transaction systems, including migrating Java services to Spring Boot microservices and adopting Kafka-based event-driven architectures. Strong focus on production reliability and operability (observability, CI/CD, standardized patterns) plus security (OAuth/JWT, RBAC, Postgres/Supabase RLS) and resilient stream processing (idempotency, DLQs).

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VK

Vikram Kini

Screened

Mid-Level Full-Stack Engineer specializing in React, TypeScript, and microservices

3y exp
I-SAFE Enterprises LLCUniversity of Illinois Urbana-Champaign

Built and productionized an AI agent-based in-app assistant at ISAFE to guide users through document workflows, piloting with a partner school district and then rolling out across districts. Combines hands-on LLM/agent debugging (logs, fallback rates, state/context tracking) with strong technical demos and sales enablement through live workflows and pilot programs (e.g., Osceola School District).

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HW

Hsi-Chun Wang

Screened

Mid-level Data Scientist specializing in LLM development and scalable ML pipelines

Remote4y exp
GearFactory.aiUniversity of Maryland, College Park

Built and deployed production LLM pipelines for evidence-based scoring in two domains: biomedical literature mining (scoring ~2700 drug compounds vs gene targets/mechanisms) and long-horizon news analytics (35 years of Chinese articles). Emphasizes reliability at scale (retries/checkpointing/validation), rigorous empirical model benchmarking (GPT-4o/mini/5), and translating results into stakeholder-friendly visual narratives.

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SP

Soham Patel

Screened

Mid-level Machine Learning Engineer specializing in healthcare NLP and MLOps

Piscataway, NJ3y exp
Syneos HealthRutgers University - New Brunswick

ML/AI practitioner in healthcare (Syneos Health) who has deployed production clinical NLP and risk models. Built a BERT-based physician-note information extraction system on Docker + AWS SageMaker (reported ~42% retrieval improvement) and automated retraining/deployment with Airflow and drift detection, while partnering closely with clinicians to drive adoption (reported ~18% readmission reduction).

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AI

Mid-level Full-Stack Java Engineer specializing in cloud-native microservices

NC, USA6y exp
Bank of AmericaUniversity of Central Missouri

Software engineer with strong full-stack and platform experience (TypeScript/React/Node.js) who has built real-time analytics dashboards and microservices using RabbitMQ. Demonstrates production-minded decision-making under launch pressure (manual fallback for payment-impacting third-party API issues) and has delivered internal DevOps tooling that automates compliance checks via GitHub/Jira integrations.

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JL

Julian Lee

Screened

Intern Software Engineer specializing in AI/LLMs and full-stack development

New York, New York1y exp
Highlight.AIUSC

AI/ML infrastructure-focused engineer who has built production RAG systems from scratch (Supabase/pgvector + OpenAI embeddings) and iterated using formal eval metrics to improve retrieval quality. Also debugged real-time audio issues in a LiveKit-based pipeline by correlating packet loss with VAD behavior, and has deep experience building brittle, customer-specific financial platform integrations in Python/Playwright (2FA, redirects, token refresh, rate limits).

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EY

Edward Yu

Screened

Senior Software Engineer specializing in FinTech, payments, and authentication

Sunnyvale, CA8y exp
MudflapUC Irvine

Software engineer with experience at Dollar Shave Club and Mudflap, focused on user-driven product delivery and cross-team alignment. Built an Okta SSO-based internal portal (React/Node) centralizing access to org services, and has hands-on experience diagnosing LLM/agent workflow issues via instrumentation and systematic triage. Known for translating between product/customer needs and engineering tradeoffs to ship quickly while planning stabilization and scalability.

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VS

Senior Full-Stack Java Developer specializing in cloud-native microservices and real-time web apps

New York, USA5y exp
SeatGeekPace University

Full-stack engineer/product owner who built and scaled a customer-facing job application portal (Skillbridge) using TypeScript/React and Spring Boot/MongoDB, optimizing search performance with indexing, caching (Redis), and payload/lazy-loading improvements. Also built an internal AI-driven analytics dashboard for Salesforce operations using OpenAI sentiment analysis, achieving 70% reduction in manual analysis and driving adoption through demos and iterative feedback.

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BC

Mid-level Full-Stack Developer specializing in React/Next.js and Node/NestJS

Remote, USA3y exp
WayfairWebster University

Full-stack engineer who built and owned an internal analytics dashboard for sales (React/TypeScript + Node/Express + NoSQL), delivering it two weeks early with zero production issues and a reported 10% sales-efficiency lift. Experienced with microservices and async messaging patterns (retries/DLQs/idempotency), and emphasizes rapid iteration with strong CI/CD and automated testing plus user-driven adoption.

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HS

Mid-level Full-Stack Software Engineer specializing in cloud-native microservices

California, USA4y exp
OracleCalifornia State University, Long Beach

Cloud-native integration engineer (Oracle/OCI) with strong production deployment and incident-response experience, including API gateway rollouts, observability (Prometheus/Grafana), and multi-layer debugging for payments systems. Built Python/FastAPI microservices and automation for customer-specific reporting and data sync, and has delivered major performance gains (45 min to <10) plus reliability improvements (MTTD reduced 40%+) through monitoring, playbooks, and resilient integration patterns (streaming/queuing, retries, secure tokens, VPC peering).

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