Vetted Amazon DynamoDB Professionals

Pre-screened and vetted.

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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YS

Yash Sanjay Zaveri

Screened ReferencesStrong rec.

Junior Software Engineer specializing in backend systems and AI automation

Boston, MA2y exp
Northeastern UniversityNortheastern University

Built and deployed an AI Copilot for Healthful Telehealth that helps dietitians generate personalized meal plans using patient data and real-time clinical context. Stands out for owning the full lifecycle—from workflow discovery and ETL/RAG architecture to production incident response and post-launch stabilization—while delivering roughly 30% gains in retrieval accuracy and latency.

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VK

Vamsi Krishna Chigurupati

Screened ReferencesModerate rec.

Mid-level Full-Stack Developer specializing in FinTech microservices

USA4y exp
CitigroupUniversity of Alabama at Birmingham

Backend engineer currently at Citigroup working on real-time transaction processing systems with Kafka. Stands out for using AI tools pragmatically in a regulated banking environment to improve debugging, testing, and developer productivity while keeping human control over architecture, security, and performance decisions.

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Manasa Pantra - Junior Software Engineer specializing in AI, LLM systems, and full-stack development in Stony Brook, NY

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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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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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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SS

Shubham Singh

Screened

Senior Software Engineer specializing in cloud-native microservices and healthcare integrations

USA6y exp
CVS HealthIndiana University Bloomington

Backend engineer at Cerebrone.ai building cloud-native Flask microservices for an AI-driven automation platform on GCP (Cloud Run/App Engine), including dedicated inference services integrating OpenAI and internal ML pipelines. Demonstrated strong performance and scalability wins across Postgres/SQLAlchemy optimization, multi-tenant (healthcare/HIPAA-grade) data isolation, and high-throughput background processing with Celery/Redis/RabbitMQ, with multiple quantified latency/CPU/throughput improvements.

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AR

Anurag Reddy

Screened

Mid-level Data Scientist specializing in ML, MLOps, and Generative AI

TX, USA5y exp
CaterpillarUniversity of Illinois Chicago

ML/NLP engineer who built a RAG-based technical assistant for Caterpillar field engineers, transforming PDF keyword search into intent-based semantic retrieval across manuals, logs, sensor reports, and technician notes. Strong in productionizing data/ML systems (Airflow, PySpark) with rigorous preprocessing, entity resolution, and evaluation—delivering measurable gains in accuracy, relevance, and duplicate reduction.

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DW

David Wisdom

Screened

Mid-level Data & Machine Learning Engineer specializing in production ML and data platforms

San Francisco, CA5y exp
Spice DataWilliam & Mary

Built and deployed a production LLM system that scraped Google Maps menu photos, extracted structured prices via OpenAI, and cross-validated them against website-scraped data to automate data-quality verification at scale (replacing costly manual contractor checks). Demonstrates strong reliability instincts—precision-first prompting, output gating with image-quality metadata, and fuzzy matching/RAG techniques—plus solid orchestration (Dagster/Airflow) and observability (Sentry, Prometheus/Grafana).

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SS

Sarthak Singh

Screened

Mid-level Full-Stack Engineer specializing in cloud-native systems and LLM applications

Remote, USA4y exp
InfluencedUniversity of Maryland, College Park

Customer-support/engineering background spanning Informatica PowerCenter ETL and IBM demos/workshops, with hands-on experience hardening data workflows for production (error tables/reject links, validation, restart strategies, alerting, performance tuning). Also demonstrates a clear, systems-level approach to diagnosing LLM/agentic workflow issues (prompt/RAG/tooling/memory) using instrumentation and iterative fixes, and has partnered with sales on POCs by defining success metrics and mapping solutions to customer architectures.

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RP

Rubesh Phaiju

Screened

Senior Full-Stack Java Engineer specializing in cloud-native microservices and GenAI

Mechanicsburg, PA8y exp
DeloitteUniversity of the Cumberlands

Deloitte engineer who built and shipped AI-powered, Kafka-driven workflow automation for transportation/document processing, including LLM-based semantic search. Strong in production reliability (idempotency, offset management, retries), observability (Datadog/CloudWatch), and database performance tuning (PostgreSQL/Flyway), with measurable latency improvements.

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AB

Ananya Bojja

Screened

Mid-level AI/ML Engineer specializing in healthcare analytics and MLOps

USA4y exp
CignaUniversity of New Hampshire

AI/ML engineer at Cigna Healthcare building a production, HIPAA-compliant LLM-powered clinical insights platform that summarizes unstructured medical notes using a fine-tuned transformer + RAG on AWS. Demonstrates strong end-to-end MLOps and cloud optimization (distillation, Spot/Lambda/Auto Scaling) with quantified outcomes (~28% accuracy lift, ~40% less manual review, ~25% lower ops cost) and strong clinician-facing explainability via SHAP and dashboards.

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RN

Mid-Level Software Engineer specializing in Python backend, data engineering, and cloud microservices

New Jersey, USA6y exp
Abacus InsightsNJIT

Backend-leaning full-stack engineer with production experience in both healthcare (claims enrichment/interoperability at Abacus) and finance (Goldman Sachs pricing/risk APIs + React dashboards). Built an event-driven AI grading platform using Postgres Debezium CDC + Kafka + FastAPI on AWS that cut manual grading ~70% and served 1000+ students, with strong emphasis on reliability, testing, and performance tuning.

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SR

Senior Cloud/DevOps Engineer specializing in Azure, Kubernetes, and Infrastructure as Code

Virginia, US5y exp
Electrify AmericaGeorge Mason University

Azure cloud platform engineer with strong enterprise Linux operations background who designs multi-region HA/DR on Azure (and AWS) using Azure Site Recovery, Traffic Manager, AKS autoscaling, and geo-replicated Azure SQL. Built secure Azure DevOps CI/CD pipelines for .NET/Python microservices to AKS/VMs and provisions full environments via Terraform modules with remote state, drift checks, and staged rollouts; has not directly owned IBM Power/AIX at scale.

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SG

Mid-level Generative AI Engineer specializing in LLM systems and RAG

5y exp
Huntington BankCentral Michigan University

Currently at Huntington Bank, built a production-grade RAG system that helps business/operations teams get grounded answers from large volumes of internal enterprise documents. Owns ingestion and FastAPI backend, tuned hybrid BM25+vector retrieval and chunking for relevance, and evaluates reliability with metrics and observability (LangSmith, CloudWatch, Prometheus/Grafana) while partnering closely with non-technical stakeholders.

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NT

Mid-level Full-Stack Java Developer specializing in cloud-native microservices and data streaming

Atlanta, GA6y exp
VisaMissouri University of Science and Technology

Software engineer with payments-domain experience (Visa) building real-time transaction monitoring and analytics systems. Strong end-to-end ownership across Spring Boot/Kafka microservices, PostgreSQL modeling, and AWS/Kubernetes operations, plus React+TypeScript dashboards—focused on low-latency processing, secure APIs, and zero-downtime production releases.

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SS

Shivam Sah

Screened

Mid-level Backend Software Engineer specializing in distributed microservices

New York, United States4y exp
ActiveViamNortheastern University

Internship at ActiveVM where they tackled large-scale Spring Boot 2→3/library migrations across hundreds of downstream products by combining OpenRewrite (AST-based recipes) with an LLM/RAG-based classifier that routed risky files to human experts. Reported ~70% reduction in manual effort and 90%+ accuracy after testing across multiple branches and cutovers; also built a CTR-driven book recommendation capstone showcased at the Google office in Cambridge.

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MG

Senior Data Engineer specializing in cloud data platforms and real-time streaming

6y exp
HCA HealthcareWright State University

Data engineer in healthcare (HCA) who owned end-to-end Azure-based pipelines at very large scale (50M+ daily claims/patient records). Strong focus on reliability: schema-drift fail-fast validation, quarantine layers, and Python/SQL data quality checks that reduced issues ~25%, plus performance tuning in Databricks/PySpark and versioned serving in Synapse for downstream consumers.

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Danilo Plazas - Senior Full-Stack Software Engineer specializing in Frontend (React/JavaScript) in Vancouver, Canada

Danilo Plazas

Screened

Senior Full-Stack Software Engineer specializing in Frontend (React/JavaScript)

Vancouver, Canada10y exp
PaycorUniversidad Libre

Frontend-focused engineer with full-stack experience who modernized a legacy HR platform (CoffeeScript/Marionette) by migrating key UIs to React/Redux and adding TypeScript for robustness. Built an internal client monitoring tool end-to-end with a microservices-oriented approach and strong testing practices (Jest/Selenium), and also led a major GraphQL v1→v2 migration delivered incrementally over ~6 weeks while optimizing Django/MySQL/DynamoDB performance.

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Sravanti Dandu - Mid-level Cloud Engineer specializing in AWS & Azure infrastructure automation in Arizona, USA

Mid-level Cloud Engineer specializing in AWS & Azure infrastructure automation

Arizona, USA6y exp
American ExpressNorthern Arizona University

Backend/platform engineer (American Express) who built a Flask-based orchestration layer to automate infrastructure provisioning and integrated Azure AD/JWT RBAC security. Strong in PostgreSQL/SQLAlchemy performance optimization (70%+ query-time reduction) and scalable async/event-driven architectures, including ML inference pipelines (SageMaker/Azure ML/Hugging Face) and high-throughput job queues (Celery/Redis) with reliability patterns like DLQs and idempotency.

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JK

Jacob Kuder

Screened

Senior DevSecOps & Platform Leader specializing in cloud-native infrastructure

Williamston, SC18y exp
Booz Allen HamiltonSouthern Wesleyan University

Cloud-focused platform/infrastructure engineer centered on AWS and Kubernetes, with hands-on experience building EKS environments via Terraform/Terragrunt, bootstrapping clusters with Cilium and ArgoCD, and integrating persistent storage and backup tooling like EFS/EBS CSI and Velero. While no longer focused on on-prem or hybrid operations, they also bring prior VMware/Hyper-V and migration-to-AWS experience, making them strongest in modern cloud platform engineering roles.

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PL

Director-level engineering leader specializing in e-commerce platforms and operational systems

Brooklyn, NY6y exp
RevivnWashington and Lee University

Builder-minded founder who co-started Renew-IQ, an insurtech company that landed successful pilots with major insurance brokerages and wholesalers without raising capital. Demonstrated practical enterprise product judgment by overcoming adoption challenges through integration with required compliant systems, improving user satisfaction, communication, and efficiency.

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Gnaneswar Markat - Mid-level Software Engineer specializing in cloud-native distributed systems in Charlotte, NC

Mid-level Software Engineer specializing in cloud-native distributed systems

Charlotte, NC4y exp
Bank of AmericaUniversity at Buffalo

Full-stack engineer with Bank of America experience building and owning a customer portfolio dashboard end-to-end, from requirements through launch and ongoing iteration. They combine React/Spring Boot/PostgreSQL implementation with strong performance tuning, real-time data handling, and UX improvements, and cite adoption by roughly 12,000 active internal users.

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