Vetted SOAP Professionals

Pre-screened and vetted.

RV

Senior Machine Learning Engineer specializing in NLP, Generative AI, and healthcare/legal AI

Charlotte, NC9y exp
CuriousVector LabsNYU
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CHIRAG ARORA - Senior Backend Software Engineer specializing in microservices and cloud platforms in San Jose, CA

CHIRAG ARORA

Screened

Senior Backend Software Engineer specializing in microservices and cloud platforms

San Jose, CA9y exp
PayPalSan José State University

Backend engineer with PayPal experience building a high-reliability onboarding API platform (Java/Spring Boot) integrating KYC/compliance and serving 1M+ users annually. Also shipped an internal LLM-driven developer tool that automates PR review insights and OpenAPI documentation with rigorous evaluation, schema-bound guardrails, and production observability.

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KM

Junior Full-Stack Software Developer specializing in cloud APIs and data platforms

Calgary, Canada2y exp
DV8 EnergyUniversity of Waterloo
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Sravani Raghavaraju - Mid-Level Full-Stack Software Engineer specializing in microservices and fraud detection in Texas, USA

Mid-Level Full-Stack Software Engineer specializing in microservices and fraud detection

Texas, USA4y exp
PayPalUniversity of North Texas
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Pranav Thorat - Mid-level Machine Learning Engineer specializing in MLOps and applied AI in Seattle, WA

Mid-level Machine Learning Engineer specializing in MLOps and applied AI

Seattle, WA5y exp
Hextropian Systems Inc.NYU
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JR

Senior QA/UAT & Integration Test Manager specializing in enterprise platforms and data migration

23y exp
Booz Allen Hamilton
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WW

Senior QA Engineer specializing in automation and API testing

Los Angeles, CA9y exp
Riot GamesUSC
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MS

Mid-level Full-Stack Java Developer specializing in Financial Services

NJ, USA4y exp
Goldman SachsNJIT
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JL

Senior .NET Full-Stack Engineer specializing in healthcare cloud platforms

Wesley Chapel, FL9y exp
Mayo ClinicUniversity of South Florida
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SP

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

Canada6y exp
Rediron TechnologiesCambrian College
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SG

Mid-level Java Developer specializing in Spring Boot microservices (FinTech & Healthcare)

5y exp
PNCPace University
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RR

Senior Full-Stack .NET Engineer specializing in FinTech payments and event-driven microservices

Dallas, TX13y exp
BestowUniversity of Texas at Austin
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VD

Mid-level Workday HCM Analyst specializing in HRIS, payroll, and benefits systems

Dayton, OH4y exp
CareSourceUniversity of Cincinnati
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CN

Mid-Level Software Engineer specializing in Java, Spring Boot, and AWS

USA4y exp
Progress SolutionsUniversity of Michigan

Built and deployed a production credit card fraud detection platform that scores transactions in real time using TensorFlow/scikit-learn models exposed via a Spring Boot REST API, with strict SLAs, fallback to legacy rules, and Splunk-based monitoring/drift tracking. Also has enterprise orchestration experience with TIBCO BusinessWorks (BW 6.6/BWCE), coordinating REST/SOAP services and JMS messaging (TIBCO EMS) with robust error handling and compensation logic.

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SB

Silpa Bhavani

Screened

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

Oakland, CA5y exp
BlockLamar University

Software engineer with strong compliance-domain experience who built a customer-facing compliance and reporting dashboard using React/TypeScript with Spring Boot microservices. Demonstrates mature production engineering practices—contract-first APIs, event-driven architecture (Kafka/RabbitMQ), caching (Redis), and robust CI/CD + observability (Prometheus/Grafana/ELK)—and also created a Python-based audit automation tool adopted into the standard release process.

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Prateek Patil - Engineering Leader specializing in Digital Health, AI, and Cloud Platforms in Santa Clara, CA

Prateek Patil

Screened

Engineering Leader specializing in Digital Health, AI, and Cloud Platforms

Santa Clara, CA16y exp
RocheIllinois Institute of Technology

Senior Engineering Manager at Roche leading two Scrum teams building internally shared (“inner-sourced”) tools and libraries for a healthcare enterprise. Has led security/compliance-first architecture decisions (e.g., Python AI modules running inside a Java container) and front-end modularization (Angular monorepo to module federation), with a strong focus on developer experience via automated Swagger/OpenAPI documentation and robust testing/versioning practices.

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Swathi Sankaran - Senior Python Full-Stack Developer specializing in cloud, data engineering, and ML/GenAI in New York, NY

Senior Python Full-Stack Developer specializing in cloud, data engineering, and ML/GenAI

New York, NY10y exp
East West BankJawaharlal Nehru Technological University

Backend/data engineer with hands-on production experience building FastAPI services on AWS and implementing strong reliability/observability (CloudWatch, ELK, correlation IDs, alarms). Has delivered serverless + container solutions with IaC (CloudFormation/Terraform) and Jenkins CI/CD, and built AWS Glue/PySpark pipelines into S3/Redshift with schema-evolution and data-quality safeguards; demonstrated large-scale SQL tuning (45 min to 3 min on a 500M-row workload).

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NT

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

Downingtown, PA5y exp
Pike SolutionsNYU

Backend engineer with experience at Comcast and in healthcare/pharmacy automation (PrimeRx), building Python/Flask services that orchestrate large-scale batch workflows (Airflow) and high-throughput event processing (Kafka). Demonstrated measurable performance wins (cut provisioning latency to ~150–200ms) and strong multi-tenant isolation strategies (Postgres RLS, partitioning), plus practical integration of ML model outputs into production systems with validation and fallback controls.

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Allan Farinas - Senior Full-Stack Software Engineer specializing in Python and AWS in West Covina, CA

Allan Farinas

Screened

Senior Full-Stack Software Engineer specializing in Python and AWS

West Covina, CA11y exp
CareRevCal Poly Pomona

Backend/data engineer who has built production Python microservices (FastAPI) and AWS-native platforms for event ingestion and analytics, combining ECS/Fargate + Lambda with CloudFormation-driven environments and strong secrets/IAM practices. Experienced modernizing legacy logic with parallel-run parity validation and safe phased cutovers, and has demonstrated measurable SQL tuning wins (20–30s down to 1–2s) plus incident ownership in Glue/Step Functions ETL pipelines.

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SR

Mid-Level Java/Full-Stack Engineer specializing in FinTech and cloud-native microservices

Pittsburgh, PA5y exp
Capital OneGannon University

Software engineer/product-focused builder who has delivered customer-facing dashboards (React/TypeScript + Spring Boot) and microservices using RabbitMQ, emphasizing safe, fast iteration with CI/CD, feature flags, and monitoring. Also built an internal monitoring/reporting tool adopted by ops/support by involving users early and iterating based on feedback.

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SG

Mid-Level Software Engineer specializing in secure cloud microservices and FinTech

Remote, USA4y exp
BrexSyracuse University

Built and owned major parts of a real-time distributed AI fraud-detection pipeline (ingestion, inference microservice integration, and automated action layer), optimizing latency and observability and reducing false positives by ~35%. Understands ROS/ROS2 concepts (nodes/topics/services) and planned hands-on ramp-up via ROS2 pub/sub exercises and Gazebo simulation, but has not worked on physical robots or ROS in production.

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Mahesh Kumar Duvvuri - Senior Full-Stack Software Engineer specializing in microservices and cloud-native systems in New York City, NY

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

New York City, NY4y exp
JPMorgan ChaseUniversity of Dayton

Backend/infra engineer with experience across Nestle, J.P. Morgan, and Capgemini, combining ML systems work (YOLOv8/PyTorch object detection with TFLite edge deployment) with production-grade cloud/Kubernetes operations. Has delivered measurable impact via AWS migrations (25% cost reduction, 99.9% availability), microservice modernization (35% faster processing), and low-latency Kafka streaming for financial dashboards (<100ms) using DLQs and idempotent consumers.

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