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Vetted Amazon EC2 Professionals

Pre-screened and vetted.

KM

Kimberly Michela

Screened ReferencesStrong rec.

Junior Full-Stack Software Engineer specializing in web apps and developer tools

Toronto, Canada1y exp
Game of StreaksUniversity of Toronto

Frontend engineer who built the full frontend for gameofstreaks.com using React/Next.js with an emphasis on responsive design, accessibility, SEO, and performance profiling. Has experience refactoring legacy HTML/CSS/JS sites into reusable React components and shipping quickly with unit tests, CI/CD, and branch-based deployments; also collaborates with designers in hackathon settings (e.g., an AI interview practice app).

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KP

KrishnaVarshith Pabbisetty

Screened ReferencesStrong rec.

Mid-level Backend Software Engineer specializing in Spring Boot, microservices, and cloud-native AI

Bay Area, CA4y exp
TemenosSan José State University

Backend engineer with experience modernizing a large-scale procurement platform at Jio Platforms by breaking a monolith serving 35 business units into Spring Boot microservices, improving uptime and cutting report latency ~30%. Also built high-concurrency FastAPI systems (200ms at ~500 concurrent users) with strong security (JWT/OAuth2/RBAC), event-driven Kafka integrations, and reliability patterns like exactly-once delivery for ~1M monthly triggers.

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RO

Rafael Ortega

Screened ReferencesStrong rec.

Senior Full-Stack & AI Engineer specializing in LLM integrations and cloud-native systems

Remote (Texas)8y exp
BlocUnitedNew Mexico Tech

Backend/data engineer with hands-on production experience building FastAPI Python APIs and AWS-native platforms (Lambda/API Gateway, SQS, ECS Fargate) with Terraform + GitHub Actions CI/CD and strong reliability practices (JWT/RBAC, retries/timeouts, structured errors/logging). Also built AWS Glue ETL pipelines (S3/RDS to curated S3/Athena) with schema evolution and data quality controls, modernized legacy processing via parallel-run validation and phased cutovers, and has demonstrated SQL tuning impact (seconds to <200ms) plus incident ownership for batch pipeline SLAs.

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SH

Sai Haritha Sardena

Screened ReferencesStrong rec.

Mid-level Full-Stack Software Engineer specializing in web, cloud, and AI/ML

Remote, USA7y exp
Tylmen TechNorthern Arizona University

Software engineer with experience at Wipro and Tylmen Tech owning customer-facing onboarding and real-time features end-to-end (React + Spring Boot) and building TypeScript/React apps backed by Node.js microservices (MongoDB, RabbitMQ). Strong in production reliability and fast iteration: feature-flagged rollouts, idempotent APIs/consumers, DLQs, and SLO-driven incident tooling, including an internal QA & release dashboard adopted by engineering and support teams.

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BH

Bryan Holland

Screened ReferencesStrong rec.

Executive AI Product & Controls Engineering Leader specializing in agentic video editing and EV systems

SF Bay Area, CA11y exp
MAGICSEVEN AIUniversity of Michigan

Startup builder (MagicSeven) who designed and implemented a browser-based, agentic video editor end-to-end, including an AWS event-driven multimodal LLM “indexing” pipeline and an orchestration LLM agent for searching and manipulating footage. Demonstrates deep video file/codec knowledge plus practical production hardening of LLM workflows (format validation, plan/execute, S3-based state for debuggability).

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VS

Vigneshwari Shankiri

Screened ReferencesStrong rec.

Senior Java Full-Stack Developer specializing in microservices and cloud platforms

5y exp
TD BankSt. Peter's Engineering College

Frontend engineer who has led enterprise-scale UI delivery end-to-end on a microservices platform, designing modular Angular SPAs (v12-17) tightly aligned to Spring Boot REST APIs. Emphasizes quality and release velocity through layered testing (Karma/Jasmine), CI/CD automation (Jenkins/Azure DevOps), performance tuning with RxJS/lazy loading, and incremental rollouts with close product/design/QA collaboration.

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NR

Nithin Reddy

Screened

Mid-Level Software Development Engineer specializing in distributed systems and event-driven architectures

Santa Clara, California4y exp
Goldman SachsCentral Michigan University

Built and maintained an internal JavaScript/React real-time event monitoring UI used by multiple Goldman Sachs teams (e.g., Private Wealth Management and Bulk Trading Systems). Focused on scaling performance under hundreds of events/sec—using profiling, memoization, batching, and debouncing—and paired it with strong internal documentation and disciplined incident diagnosis via synthetic load testing and logs/metrics.

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MS

Mid-level Full-Stack Developer specializing in Next.js, AI-driven apps, and payments

Calgary, AB4y exp
Dasens AIUniversity of Waterloo

Frontend engineer who has led complex React + TypeScript products end-to-end, including a real-time canvas-based digital signature editor and a multi-step AI workflow dashboard. Demonstrates strong architecture and performance instincts (state machines for streaming async updates, bundle/render optimizations) plus pragmatic shipping practices (feature flags, automated tests, analytics and user interviews), with a quantified impact from refactoring (~30% less duplicated UI code).

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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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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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MS

Senior Software Engineer specializing in robotics, ML, and full-stack web development

Hillsboro, OR12y exp
IntelPortland State 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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VV

Vaishnavi Veerkumar

Screened ReferencesStrong rec.

Mid-level AI Engineer specializing in GenAI and RAG systems

Boston, MA4y exp
VizitNortheastern University

AI engineer who built a production e-commerce system that analyzes product images alongside sales and demographic data to generate actionable creative recommendations, now used by 20+ clients. Also built orchestrated document/agent pipelines (Airflow, LangGraph) including a compliance drift detector auditing 401 compliance documents, with an emphasis on traceability, logging, and production integration.

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JL

Joseph Lin

Screened ReferencesModerate rec.

Intern Software Engineer specializing in full-stack development and applied AI

New York, NY0y exp
Real Value CapitalNYU

Internship experience building an end-to-end medical AI pipeline that extracts and normalizes messy medical PDFs, fine-tunes BioBERT to classify tumor-related statements (including negation/ambiguity handling), and integrates image-model outputs (MedSAM/GroundingDINO) for tumor localization and classification. Also worked on an LLM/RAG system to draft IPO prospectuses using retrieved regulatory/financial sources (including SEC EDGAR) with structured prompts to reduce hallucinations.

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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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