Vetted Amazon EC2 Professionals

Pre-screened and vetted.

Harika Reddymalle - Mid-Level Full-Stack Software Engineer specializing in backend automation and insurance systems in Dallas, TX

Mid-Level Full-Stack Software Engineer specializing in backend automation and insurance systems

Dallas, TX4y exp
MetLifeSaint Leo University

Full-stack engineer with hands-on production ownership across Angular/.NET/SQL and React+TypeScript/Node/Postgres stacks, including CI/CD and AWS operations (EC2/ECS, RDS, S3, CloudWatch). Delivered an internal insurance document upload and tracking feature end-to-end, adding audit/history and async processing, then validated success through monitoring metrics and reduced support tickets. Comfortable shipping MVPs in ambiguous environments using feature flags, strong validation, and backward-compatible database migrations.

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AneeshReddy Kusa - Junior Full-Stack Software Engineer specializing in React and FinTech in Hyderabad, India

Junior Full-Stack Software Engineer specializing in React and FinTech

Hyderabad, India2y exp
CognizantUniversity of Cincinnati

Full-stack engineer with banking-domain experience (Cognizant/Kotak) building and optimizing high-usage transaction/account APIs on Spring Boot/Node/PostgreSQL in AWS/Docker, including peak-load performance fixes. Also built an end-to-end retail demand-forecasting feature during a master’s program, spanning data pipelines, ensemble models, dashboards, and operational guardrails like validation and fallbacks.

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Sivapriya Rachakonda - Mid-Level Software Engineer specializing in cloud-native microservices on AWS and Kubernetes in Remote, USA

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

Remote, USA5y exp
OptumUniversity of South Dakota

Backend engineer who built a stateless Python/Flask service supporting a healthcare-document ETL pipeline, offloading heavy processing to Celery workers and adding strong observability (metrics, structured logs, audits). Demonstrates practical performance/reliability work: batch chunking, priority queues, autoscaling by queue depth/CPU, DLQ routing, and PostgreSQL tuning (indexes, pagination) to cut slow API responses. Also has experience deploying real-time ML classification via TensorFlow Serving behind a FastAPI wrapper and integrating models via REST/gRPC.

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Valeriy Filin - Senior Backend/Cloud Engineer specializing in IaC, SaaS platforms, and ML/Computer Vision in Aliso Viejo, CA

Valeriy Filin

Screened

Senior Backend/Cloud Engineer specializing in IaC, SaaS platforms, and ML/Computer Vision

Aliso Viejo, CA19y exp
IT Rex GroupOdessa National Polytechnic University

Backend/infrastructure engineer with experience across API development (FastAPI/MySQL/SQLAlchemy), Kubernetes deployments, and large-scale data processing—built a Dockerized Python pipeline to pre-aggregate ~1B Graylog events for efficient querying. Has enterprise infrastructure automation background at Hewlett Packard Enterprise (Datafabric) using Terraform/Ansible with fail-fast and rollback practices, plus Kafka-based sensor streaming prototypes to Google Cloud with Java workers and autoscaling.

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Rahul Solleti - Mid-Level Software Engineer specializing in cloud-native microservices and full-stack web apps in United States

Rahul Solleti

Screened

Mid-Level Software Engineer specializing in cloud-native microservices and full-stack web apps

United States5y exp
Dell TechnologiesUniversity of Central Missouri

Backend/platform engineer focused on real-time financial fraud detection and transaction monitoring, building low-latency FastAPI + Kafka systems with strong reliability patterns (DLQs, idempotency) and cloud observability. Has hands-on Kubernetes delivery across AWS EKS and Azure AKS with automated CI/CD and GitOps-style deployments, plus experience migrating legacy C# / Java monoliths to containerized microservices using Terraform/ARM and zero-downtime rollout strategies.

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SK

Intern Software Engineer specializing in cloud, full-stack, and AI systems

United States1y exp
Five9California State University, East Bay

Built a production LLM-assisted workflow for customer configuration data migrations, combining agentic parsing with deterministic validation and fail-safe pipeline design. Stands out for turning messy ERP and operational data into reliable, repeatable transformations while improving accuracy and cutting manual effort by more than 80%.

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PS

Mid-level Full-Stack Engineer specializing in FinTech deployments

4y exp
BMOUniversity of Central Missouri

Backend-focused engineer with banking-domain deployment experience who has owned releases end-to-end, from discovery and API/database implementation through post-launch stabilization. Brings a reliability-first mindset across distributed systems, incident response, and messy real-world data handling, and has also applied that foundation to retrieval-based LLM workflows in production-oriented cloud environments.

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NK

Mid-level Backend Engineer specializing in APIs, microservices, and data platforms

High Point, NC6y exp
AtosNortheastern University

Software engineer who built JobIntel, an end-to-end Python ETL pipeline integrating ATS data from platforms like Greenhouse using Scrapy and FastAPI. Stands out for production reliability work: designing async fault-tolerant architecture, optimizing PostgreSQL write-heavy upserts, and building a Prometheus/Splunk observability stack that cut debugging from hours to minutes.

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KB

Keerthi Basam

Screened

Mid-level Software Engineer specializing in AI/ML for FinTech and Healthcare

United States4y exp
IBMWright State University

Built and deployed an end-to-end fintech product, FinSight, for bank statement analysis and financial Q&A using a production-style RAG architecture. Stands out for combining FastAPI, OpenAI embeddings, FAISS, hybrid SQL/vector retrieval, and practical reliability work like chunking optimization, validation, and low-latency performance tuning.

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VN

Senior Full-Stack Software Engineer specializing in backend systems and cloud-native APIs

Detroit, MI7y exp
CortileSan Jose State University

Full-stack engineer with startup-style ownership across backend, frontend, and AI systems, spanning Java/Spring, React, Node/TypeScript, and LLM-powered retrieval. Shipped a workspace intelligence layer using LangChain, OpenAI, and Pinecone to paying customers, while also improving core product metrics like workspace creation success (+30%), latency (450ms to 280ms), and deployment cycle time (-40%).

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DK

Mid-level AI/ML Engineer specializing in applied AI for banking and healthcare

Kentwood, MI5y exp
Fifth Third BankUniversity of Central Missouri

Built end-to-end AI products across fintech and healthcare, including a real-time loan risk prediction system and a patient feedback insights platform. Stands out for combining full-stack delivery, production ML/MLOps on AWS, and pragmatic human-in-the-loop safeguards; reported a 22% improvement in prediction accuracy.

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TS

Tej Sidda

Screened

Entry-level Full-Stack Engineer specializing in AI sales automation

Dallas, TX1y exp
CellaNova TechnologiesNortheastern University

Built both a fantasy sports analytics product and a privacy-sensitive AI assistant for therapists, showing range across consumer and healthcare use cases. Particularly notable for designing self-hosted, HIPAA-conscious LLM systems with RAG, structured outputs, observability, and human-in-the-loop guardrails for clinical workflows.

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MB

Senior AI Engineer specializing in machine learning, IoT, and data platforms

Winterville, NC16y exp
FreelanceEast Carolina University

Backend/cloud engineer who built an AWS serverless IoT system that computes Bluetooth beacon locations from telemetry using heavy scientific Python (NumPy/SciPy/pandas) packaged as Dockerized Lambda, integrated with Java microservices and scheduled batch orchestration. Has deep AWS delivery experience (CI/CD with Code* tools, CloudFormation, cost controls) and has led high-severity incident response including CloudTrail forensics and infrastructure recovery after a compromised-keys crypto-mining attack.

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MB

Mark Brown

Screened

Junior Full-Stack Software Engineer specializing in mobile, web, and cloud

Hyannis, MA2y exp
Savant SystemsUniversity of Connecticut

Built a senior design project for Webquity LLC: a React/TypeScript Chrome extension and web app helping students with ADHD manage focus, tasks, and productivity across devices. Stands out for combining performance tuning, cross-device sync, accessibility-minded UX research, and polished UI touches like theming, weather-reactive backgrounds, and Lottie-based mascot animations.

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SD

Mid-level Full-Stack Developer specializing in cloud-native web applications

Dallas, TX4y exp
ScienceSoftClemson University

Full-stack engineer with strong ownership across React, FastAPI, and PostgreSQL who has built real-time collaboration and analytics workflows end-to-end. Particularly compelling for high-growth AI product teams: they’ve also shipped a 0→1 AI-assisted dataset retrieval and summarization capability, balancing MVP speed with scalable architecture and post-launch performance tuning.

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SR

Shahbaz Raza

Screened

Mid-level Software Engineer specializing in ML infrastructure and cloud-native data platforms

Lahore, Pakistan4y exp
MotiveNational University of Computer and Emerging Sciences

Backend/data engineer focused on high-scale, event-driven AWS ingestion systems (SQS/Lambda/EKS) processing millions of events per day, with strong reliability patterns (idempotency, DLQs, bounded retries) and deep observability using Datadog distributed tracing. Has delivered Terraform/GitHub Actions CI/CD and improved secret rotation via Secrets Manager + IRSA, plus Glue-based ETL with schema-evolution handling and Postgres SQL optimization (including JSONB/GIN indexing). Candidate is currently living outside the US and states they do not have US work authorization.

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SR

Mid-level Full-Stack Software Engineer specializing in cloud-deployed web apps and APIs

Dayton, OH3y exp
Wells FargoWright State University

Software engineer who has shipped both core web platform features (secure user authentication/profile management) and production LLM systems. Built an internal documentation knowledge assistant using a full RAG pipeline (OpenAI embeddings, vector DB, semantic search, reranking) with evaluation loops and a scalable document-ingestion pipeline for PDFs/FAQs, iterating based on metrics and user feedback.

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KH

Kenny Ho

Screened

Mid-level Full-Stack Developer specializing in React, monorepos, and AWS

Burnaby, Canada5y exp
South Vancouver Medical ClinicUniversity of British Columbia

Frontend/product engineer who has led end-to-end builds across automotive and healthcare: created a multi-tenant, high-performance Next.js luxury inventory platform and a secure, Stripe-powered sick-note workflow integrated with an EMR. Known for data-driven UX decisions (A/B testing) and pragmatic modernization of critical systems (3DS2 upgrade) with measurable conversion and risk improvements.

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AG

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

Austin, TX3y exp
PurevisitxUniversity of Illinois Springfield

ML/AI engineer who built and productionized an NLP system at PurevisitX, orchestrating end-to-end ML workflows with Airflow (S3 ingestion through auto-retraining) and optimizing for drift and low-latency inference. Also partnered with Citibank risk teams on a fraud detection model, translating results via dashboards and iterating thresholds based on stakeholder feedback.

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MK

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

Edison, NJ4y exp
PointelArizona State University

Backend-focused engineer who owned an end-to-end Python/Flask service at Viasat powering a 1000+ user internal React app, including API design, Postgres performance tuning (~50% faster), Dockerization, and CI/CD. Demonstrated strong problem-solving by building custom EDN parsing logic and has built near real-time AWS SQS/Lambda pipelines with DLQs and autoscaling patterns; currently ramping on Kubernetes/GitOps (ArgoCD).

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MS

Manoj Suggala

Screened

Mid-level Software Engineer specializing in cloud-native microservices for FinTech and Insurance

Texas, USA3y exp
AIGGeorge Mason University

Backend engineer who owned an order management API built with Python/FastAPI and PostgreSQL, integrating payment and shipping providers with strong reliability patterns (idempotency, async workers, retries/backoff, circuit breakers). Experienced deploying services to Kubernetes using a GitOps model with ArgoCD (auto-sync, self-healing, pruning, rollbacks) and building high-volume Kafka streaming pipelines. Has also supported phased cloud-to-on-prem migrations with a focus on security monitoring/SIEM log continuity.

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BT

Mid-Level Software Engineer specializing in AI automation and full-stack FinTech

6y exp
AccentureGeorge Washington University

Built an AI-powered loan automation dashboard using React and open-source JavaScript libraries, with hands-on experience improving real-world performance by reducing re-renders and optimizing/caching multiple API calls. Also produced developer-friendly API documentation for a voice assistant project, helping teammates integrate features faster with fewer errors.

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VS

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

WI, USA5y exp
HCLTechWright State University

Product-focused full-stack engineer (Spring Boot/Django + React/TypeScript) with deep experience building multi-tenant, enterprise workflow and supply-chain/order-tracking systems. Owned an end-to-end Workflow SLA Breach Prediction & Alerting feature integrating Azure ML for a cloud workflow platform used by ~10,000 enterprise users, and has hands-on AWS operations experience resolving real production latency/scaling incidents via query optimization and Redis caching.

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PK

Mid-Level Full-Stack Software Engineer specializing in cloud-native microservices and data analytics

Oklahoma City, USA5y exp
Wells FargoOklahoma City University

Software engineer with experience at Wipro Technologies and Wells Fargo building React-based SPAs, reusable component libraries, and developer documentation. Demonstrated strong performance engineering (React.memo, list virtualization, code splitting) with reported >50% rendering-time improvement, plus hands-on production support by diagnosing API outages via monitoring/logs and implementing traffic/server fixes. Comfortable leading workstreams in fast-changing environments using Kanban and tight stakeholder feedback loops.

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