Vetted AWS IAM Professionals

Pre-screened and vetted.

John Juszczak - Senior Software Engineer specializing in C++ tooling, CI/CD, and Unreal Engine pipelines in Los Angeles, CA

John Juszczak

Screened

Senior Software Engineer specializing in C++ tooling, CI/CD, and Unreal Engine pipelines

Los Angeles, CA10y exp
Starpunch StudiosDePaul University

Gameplay programmer with hands-on Unreal Engine multiplayer shooter experience, notably overhauling aiming/ADS using Enhanced Input and curve-table-driven response curves plus subtle aim assist. Demonstrates strong networking judgment (client-side prediction vs server authority for anti-cheat) and a systems mindset, adding automation/analytics to speed iteration and improve decision-making.

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Sandhya Yadavalli - Mid-level Cybersecurity Analyst specializing in SIEM, incident response, and Zero Trust in Remote, USA

Mid-level Cybersecurity Analyst specializing in SIEM, incident response, and Zero Trust

Remote, USA3y exp
BigCommerceYeshiva University

Cybersecurity/SOC-focused engineer with hands-on production experience integrating and tuning Splunk Enterprise Security for a zero-trust program, including CIM normalization, correlation/risk-based detection tuning, and performance optimization via forwarder-level filtering and index strategy. Has cross-disciplinary incident troubleshooting experience spanning SIEM, networking, and hardware, and has automated customer/team-specific security workflows using Python in Splunk playbooks; collaborated on-site with HSBC IT/SOC teams to deliver dashboards and security policies.

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PC

Pranit Chetta

Screened

Senior Full-Stack Java Engineer specializing in cloud-native AI and enterprise platforms

Wilmington, DE11y exp
JPMorgan ChaseGujarat Technological University

Full-stack product engineer who owned a live-events digital ticketing platform end-to-end, including blockchain-based ticket validation and high-traffic booking flows. Stands out for combining Angular/React frontend work with Java/Spring Boot backend architecture, plus strong production reliability practices around concurrency control, queues, observability, and UX optimization.

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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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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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Joshua Smith - Executive engineering leader specializing in AI automation and enterprise transformation in Banks, OR

Joshua Smith

Screened ReferencesStrong rec.

Executive engineering leader specializing in AI automation and enterprise transformation

Banks, OR23y exp
NexGen Data SystemsAmerican Military University

Technology leader with deep accelerator and zero-to-one product experience across the Department of Defense, Fortune 100 enterprises, academia, and GovTech. Most notably, they built a seven-tier solution that generated over $10M in first-year savings and was adopted by 300+ DoD organizations, positioning them as a strong CTO-type operator for mission-driven startups and complex enterprises.

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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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RS

Mid-level Software Engineer specializing in AI backend and FinTech

Syracuse, NY3y exp
Morgan StanleySyracuse 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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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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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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JK

Mid-Level Full-Stack Software Engineer specializing in backend-heavy systems across FinTech and telecom

4y exp
Cable OneArizona State University

Full-stack engineer who built and supported production features in a productivity/task-tracking app using Next.js App Router + TypeScript (server components for initial render, client components for interactivity, API route handlers for mutations). Also designed and optimized Postgres data models/queries and implemented resilient, event-driven payment processing with idempotency, retries, audit logs, and strong testing/observability practices.

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HV

Junior Software Engineer specializing in Full-Stack and ML for FinTech

Hyderabad, Telangana1y exp
Volksoft TechnologiesUSC

Full-stack engineer with fintech trading-platform experience who shipped and operated a real-time portfolio P&L/performance feature end-to-end (React + Node/WebSockets + MongoDB) on AWS, including significant performance tuning under peak trading load. Also built a Spark-based trading analytics pipeline with idempotency and reconciliation for auditability, and has a personal React/TS + Node/Express project (Artsy) with JWT auth and schema-evolution practices.

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NK

Senior Data Engineer specializing in Palantir Foundry and Snowflake for regulated industries

USA5y exp
American ExpressUniversity of Massachusetts Boston

Data engineer focused on high-volume transaction pipelines (2M+ per day) using Snowflake/Snowpipe, Spark/PySpark, Kafka, and Airflow, with a strong emphasis on schema/data-quality enforcement and reliability improvements. Also built a greenfield compliance-focused RAG solution, using CloudWatch monitoring and adding ingestion validation to prevent malformed OCR documents from degrading search quality.

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AG

Anagha Ghate

Screened

Mid-level Backend Software Engineer specializing in FinTech microservices

USA4y exp
JPMorgan ChaseBinghamton University

Engineer with production experience in both high-throughput banking risk systems and LLM agent platforms. Built a real-time transaction risk scoring middleware at JPMorgan Chase (1M+ requests/day) emphasizing HA, observability, and audit/PII compliance, and also architected multi-step LLM agents with strict schema-based tool calling, evaluation loops, and safety guardrails for messy enterprise data.

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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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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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Hsi-Chun Wang - Mid-level Data Scientist specializing in LLM development and scalable ML pipelines in Remote

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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MD

Mikeal Day

Screened

Executive Engineering Leader specializing in SaaS, FinTech, and AI

Seattle, WA21y exp
Nu Day ResourcesMontana Technological University

Startup-oriented product/technology leader targeting CTO roles, with experience evaluating and scoping high-impact product expansions. At Crelate, helped assess and shape a contract timekeeping/invoicing initiative that expanded TAM by hundreds of millions and increased ACV 2-3x, contributing to successful market traction and the company’s path to Series C.

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SY

Subash Yadav

Screened

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

San Francisco, CA7y exp
VisaWebster University

Backend engineer with experience at Visa and Ansel, owning cloud-native, event-driven microservices end-to-end in high-volume and business-critical environments. Stands out for combining scalable Java/Spring/Kafka architecture with strong production rigor, incident ownership, and a pragmatic approach to AI workflow integration that emphasizes guardrails over blind model trust.

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