Vetted AWS Professionals

Pre-screened and vetted.

Mike Khorrami - Director-level Engineering Leader specializing in enterprise SaaS and cloud-native platforms in Woodland Hills, CA

Mike Khorrami

Screened

Director-level Engineering Leader specializing in enterprise SaaS and cloud-native platforms

Woodland Hills, CA25y exp
BlackLineCalifornia State University, Northridge

Engineering leader/player-coach who modernized a legacy C#/SQL Server system to Snowflake + Python on GCP, enabling ~30x scale and supporting hundreds of millions of transactions per day per customer. Strong in architecture tradeoffs (Snowflake vs Databricks), production reliability (New Relic, logging/alerting), and lightweight process improvements like a rigorous Definition of Done and structured PR reviews.

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UMESH KAMISETTY - Mid-level Data Engineer specializing in cloud lakehouse and streaming platforms in Seattle, WA

Mid-level Data Engineer specializing in cloud lakehouse and streaming platforms

Seattle, WA5y exp
First United BankCleveland State University

Data engineer focused on building production-grade pipelines on AWS (Kafka/Kinesis/Glue/S3) through to curated serving layers in Snowflake and Delta Lake. Emphasizes automated data quality validation (PySpark + CI/CD), modular dbt transformations for analytics (customer spending, risk metrics), and operational reliability with CloudWatch and DLQs; data consumed by BI tools and ML pipelines for fraud detection and risk analytics.

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Sri Harsha patallapalli - Mid-level Machine Learning & Data Infrastructure Engineer specializing in MLOps on AWS in Boston, MA

Mid-level Machine Learning & Data Infrastructure Engineer specializing in MLOps on AWS

Boston, MA5y exp
Dextr.aiNortheastern University

Built and deployed a fine-tuned Qwen 2.5 14B model into production at Dextr.ai as the backbone for hotel-operations agentic workflows, running on AWS EKS with Triton and TensorRT-LLM. Demonstrates strong cost-aware LLM engineering (QLoRA, FP8/BF16 on H100) plus rigorous benchmarking/observability (Prometheus, LangSmith) with reported sub-30ms TTNT. Previously handled long-running ETL orchestration with Airflow at GE Healthcare and Lowe's.

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Divyansh Agarwal - Junior Machine Learning Engineer specializing in computer vision and LLM applications in New York, NY

Junior Machine Learning Engineer specializing in computer vision and LLM applications

New York, NY3y exp
AdeptmindNYU

Built and led an autonomous driving software effort for Formula Student, owning the full autonomy stack (perception, planning, control) orchestrated in ROS. Implemented stereo depth + YOLO object detection, RRT/RRT* planning, and a robust SLAM pipeline (Kalman filter, submapping) while leveraging Gazebo simulation and modern deployment tooling (Docker/Kubernetes, AWS, GitHub Actions CI/CD).

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Jhansi D - Senior Full-Stack Java Developer specializing in cloud-native microservices in Chicago, Illinois

Jhansi D

Screened

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

Chicago, Illinois4y exp
Bank of AmericaUniversity of Central Oklahoma

Full-stack engineer with experience building secure, cloud-native document/workflow platforms handling high-volume customer and medical data across microservices on Kubernetes. Demonstrated impact improving performance via event-driven AWS architectures (Lambda + DynamoDB Streams) and strengthening compliance/security for S3-stored documents using IAM and KMS. Has delivered end-to-end APIs and UIs using Java/Spring Boot with Angular/React, plus Docker and CI/CD.

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Uday kumar swamy - Senior Machine Learning Engineer specializing in MLOps and NLP/GenAI in Chicago, USA

Senior Machine Learning Engineer specializing in MLOps and NLP/GenAI

Chicago, USA9y exp
UnitedHealth GroupIllinois Institute of Technology

Built a production LLM-agent framework for a startup that performs daily financial/trading analysis by combining live market data with internal tools, including a centralized memory module to prevent context drift and reduce hallucinations. Also implemented an Airflow-orchestrated retail price forecasting pipeline deployed to AWS endpoints, scaling parallel workloads via Kubernetes Executor and validating systems with rigorous functional + LLM-specific metrics and cross-team collaboration.

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Aditya Agrawal - Intern Software Engineer specializing in backend systems and data engineering

Intern Software Engineer specializing in backend systems and data engineering

1y exp
Pocket FMBITS Pilani, Hyderabad

Backend/AI engineer who has built and shipped two products: Know Founder (Python/SQL/AWS) scaling to 2,000+ users in the first month, and Unifr (unifr.online), an AI search visibility engine that queries multiple LLMs and turns responses into structured brand insights. Strong in production reliability/performance (Redis caching, indexing, precomputation) and in designing agentic workflows with guardrails, validation, retries, and human escalation.

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Rasika Deodhar - Mid-level Full-Stack Software Engineer specializing in Generative AI in Dublin, Ireland

Mid-level Full-Stack Software Engineer specializing in Generative AI

Dublin, Ireland6y exp
MMC Innovation LabSt. Cloud State University

Full-stack engineer who shipped an end-to-end speech capability for an LLM chatbot UI, integrating OpenAI APIs and publishing via Google Apigee with client documentation. Has experience operating deployments with Jenkins/Kubernetes/Docker and monitoring with Datadog, and has worked in an innovation-center environment building rapid prototypes under ambiguity with tight stakeholder feedback loops.

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Mohan Naik Megavath - Mid-level Data Engineer specializing in real-time pipelines and cloud data platforms in Remote, USA

Mid-level Data Engineer specializing in real-time pipelines and cloud data platforms

Remote, USA4y exp
TruistElmhurst University

Backend engineer with hands-on experience building secure Python/Flask services (sessions, JWT, RBAC) and optimizing PostgreSQL/SQLAlchemy performance, including custom SQL using CTEs/window functions profiled via EXPLAIN ANALYZE. Also integrates LLM features via OpenAI/Azure into backend systems and improves scalability with RabbitMQ-driven async processing, caching, and multi-tenant data isolation patterns.

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KP

Mid-level Data Engineer specializing in capital markets post-trade data platforms

Whippany, NJ3y exp
BarclaysUniversity of Connecticut

Data/streaming engineer in capital markets who led an end-to-end trade settlement data product (Kafka→MongoDB→data lake) with rigorous data-quality logic and ~$175K first-year operational impact. Also built a low-latency Go-based CME market data engine feeding SOFR curve generation, using MSK on EKS with performance tuning (idempotency, compression, partitioning) to achieve sub-100ms delivery.

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AC

Senior Front-End Engineer specializing in Angular, design systems, and accessibility

Corona, CA15y exp
KaimetrixUniversity of Phoenix

Founder of Business Online Strategic Solutions Digital Marketing, a 5-year bootstrapped digital marketing and web solutions startup serving small-to-mid-sized and enterprise clients. Focused on building scalable, performance-driven web experiences (web dev, UX/UI, CRO, marketing strategy) and is actively scaling capabilities in modern front-end development and AI-assisted workflows.

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SS

Senior Data Analyst specializing in healthcare and financial analytics

Columbus, OH5y exp
NationwideWichita State University

Healthcare analytics candidate with hands-on experience turning messy claims data in Redshift and S3 into validated reporting tables, plus automating KPI workflows in Python. They’ve owned end-to-end operational analytics projects, including a claims delay analysis that improved processing efficiency by about 20%, and have experience driving stakeholder adoption of standardized metrics across dashboards.

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MOUNIKA SAI MEKALA - Junior Data Analyst specializing in financial and operational analytics in Kansas, USA

Junior Data Analyst specializing in financial and operational analytics

Kansas, USA3y exp
KPMGUniversity of Central Missouri

Analytics professional with experience at KPMG turning messy operational and financial data from SQL Server and AWS S3 into clean reporting datasets and automated Python workflows. They combine SQL, Python, Power BI, and experimentation methods to deliver stakeholder-aligned KPI dashboards and marketing performance insights with a strong focus on data integrity and reproducibility.

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AB

Junior Software Engineer specializing in full-stack, data engineering, and mobile apps

Seattle, WA3y exp
AmazonArizona State University

Built production LLM agents at Hivenue and Amazon, spanning consumer booking automation and internal data-query/reporting workflows. Stands out for combining conversational UX with strong reliability engineering—strict tool use, state machines, schema validation, idempotency, and evaluation pipelines—and can point to measurable impact including a 21% reduction in time to book and a 12% conversion lift.

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SS

Intern AI/ML Engineer specializing in full-stack and data systems

Boston, MA1y exp
ChewyUniversity of Massachusetts Amherst

Built an LLM-powered customer segmentation agent during a Chewy internship, consolidating Snowflake data into a knowledge graph so non-technical marketing users could query customer cohorts in natural language. Stands out for combining agent/tooling design with rigorous data engineering practices, including schema audits, imputation, validation layers, and idempotent pipelines on messy large-scale datasets.

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VM

Varun Mallela

Screened

Mid-level Data Analyst specializing in financial and healthcare analytics

Richardson, TX3y exp
Franklin TempletonUniversity of Colorado Boulder

Analytics professional with experience at Franklin Templeton and IQVIA India, focused on turning messy cross-system data into trusted reporting and actionable business insights. Stands out for combining SQL, Python, AWS ETL, and BI dashboards to solve data quality issues, improve investor engagement analysis, and standardize commercial reporting in financial services and pharma contexts.

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SA

Sowjanya Ande

Screened

Mid-level Business Analyst specializing in finance, insurance, and data analytics

Rhode Island, USA4y exp
Liberty MutualWilmington University

Business/data analyst with experience at KPMG and Liberty Mutual, focused on financial reporting, data quality, and analytics automation. Has built SQL and Python workflows for large transaction datasets, reduced manual reporting effort by 15+ hours per week, and translated ambiguous business questions into standardized KPIs and Power BI dashboards used for decision-making.

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HG

Harsh Gupta

Screened

Mid Software Engineer specializing in backend systems and FinTech

Mumbai, India3y exp
Oracle Financial ServicesUniversity of Florida

Backend engineer with experience spanning regulated financial systems at Oracle Financial Services and early-stage product building at Apli.ai. Has owned production onboarding infrastructure end-to-end, improved reliability through strong observability and incident response, and also built AI-backed backend workflows using AWS, Bedrock, and RAG.

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SAITEJA MALLEMPUDI - Senior Data Scientist and AI/ML Engineer specializing in GenAI and cloud ML in Chicago, IL

Senior Data Scientist and AI/ML Engineer specializing in GenAI and cloud ML

Chicago, IL6y exp
BMOLewis University

ML/AI engineer with hands-on experience owning systems from experimentation through deployment and monitoring, including a Bank of Montreal project that improved timely interventions by 12%. Also brings GenAI/RAG experience with evaluation and safety guardrails, plus clinical NLP pipeline work extracting medication data from notes for patient risk prediction.

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RT

Rekha Talla

Screened

Mid-level Full-Stack Software Engineer specializing in AI and document automation

Los Angeles, CA5y exp
IBMUniversity of North Carolina at Charlotte

Backend/AI infrastructure engineer focused on production-ready LLM systems and distributed workflows. They described building a RAG-based multi-step agent with strong reliability controls, evaluation loops, and graceful degradation that improved latency by 30%, retrieval accuracy by 15%, and reduced support workload by 40%.

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Akhila Kannegari - Mid-level AI/ML Engineer specializing in FinTech and retail ML systems in Alabama, USA

Mid-level AI/ML Engineer specializing in FinTech and retail ML systems

Alabama, USA4y exp
Wells FargoAuburn University at Montgomery

ML-focused candidate with strong Wells Fargo experience building production fraud systems and internal GenAI tools for fraud analysts. Stands out for measurable impact in fraud detection—raising recall from 71% to 88%—while also demonstrating hands-on depth across streaming infrastructure, MLOps, LLM/RAG implementation, and Python service architecture.

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Ravindrareddy B - Junior Full-Stack Java Developer specializing in enterprise web applications in Ames, IA

Junior Full-Stack Java Developer specializing in enterprise web applications

Ames, IA2y exp
T-MobileIndiana Wesleyan University

Full-stack engineer with hands-on experience building an internal telecom order-tracking/dashboard platform at T-Mobile across React, Spring Boot, and PostgreSQL. Stands out for owning features end-to-end, from scalable frontend architecture and TypeScript patterns to API design, query optimization, CI/CD, and post-launch monitoring in AWS CloudWatch.

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Mohit Sharma - Principal Salesforce Architect specializing in healthcare and patient engagement in Ewing, NJ

Mohit Sharma

Screened

Principal Salesforce Architect specializing in healthcare and patient engagement

Ewing, NJ15y exp
IBMUttar Pradesh Technical University

Salesforce lead architect working on a large J&J healthcare implementation, with hands-on ownership of security architecture, identity modernization, and Experience Cloud design in a HIPAA-sensitive environment. Particularly notable for leading a SAML-to-OpenID Connect rollout and driving reusable LWC architecture across patient and provider portals while coordinating closely with identity, DevOps, QA, and business stakeholders.

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