Vetted Role-Based Access Control Professionals

Pre-screened and vetted.

Shrey Kumar - Junior Full-Stack Software Developer specializing in web platforms and AI workflows in Dallas, TX

Shrey Kumar

Screened

Junior Full-Stack Software Developer specializing in web platforms and AI workflows

Dallas, TX1y exp
USTUC San Diego

Software engineer who built and shipped “Counsellor AI,” a production LLM-powered academic advising agent for college students using AWS Bedrock and grounded RAG over official university catalogs/policies. Emphasizes reliability through structured JSON outputs, multi-step orchestration with shared state, and strict intake/validation gates to prevent hallucinations and invalid academic plans; also has experience hardening messy telecom operational data pipelines with normalization, permissions, fallbacks, and idempotent patterns.

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Vidhi Chhatbar - Mid-level Full-Stack Engineer specializing in cloud microservices and FinTech in Los Angeles, CA

Mid-level Full-Stack Engineer specializing in cloud microservices and FinTech

Los Angeles, CA5y exp
AIGUSC

Software engineer with experience across enterprise (AIG, MSCI) and an early-stage startup (Job Map), owning production systems end-to-end. Built secure insurance microservices on Spring Boot with JWT/RBAC and AWS-based CI/CD/observability, plus Kafka streaming pipelines for financial data. Also shipped a GenAI personalization MVP using FastAPI and LLM APIs in a high-ambiguity startup environment.

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SG

Sindhu Gunti

Screened

Mid-level Full-Stack Java Developer specializing in cloud microservices and AI-driven platforms

Remote, USA5y exp
IntuitChristian Brothers University

Software engineer with Intuit experience shipping an end-to-end real-time financial insights product on AWS, using event-driven architecture with Kafka and Spark Streaming to process millions of records with low latency. Also delivers customer-facing React + TypeScript dashboards and has hands-on production operations experience, including resolving a database scaling incident via read replicas, query tuning, and connection pooling.

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DS

Mid-level Backend Software Engineer specializing in FinTech

Chennai, India3y exp
CitigroupUniversity at Buffalo

Backend engineer with Citigroup experience who built and evolved a self-service user provisioning/identity backend, cutting onboarding from 45 minutes to under 2 minutes. Demonstrates strong production-grade integration and reliability practices (isolated integrations, retries, rollback logic, heavy logging) plus secure API development in Python/FastAPI with OAuth scope-based authorization and incremental, low-risk rollout strategies.

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SC

Shujie Chen

Screened

Entry-Level Full-Stack Software Engineer specializing in web, mobile, and distributed systems

Remote0y exp
Jiangxi Arts & Ceramics Technology InstituteUSC

Backend engineer who built a Logistics-as-a-Service platform in Go, proactively refactoring a monolithic REST service into gRPC microservices to improve performance and maintainability. Led a 3-person team with disciplined code reviews, Dockerized DB migrations, and a canary-style rollout (5% traffic) monitored for latency and failures; also implemented JWT/OAuth2 RBAC and production-minded edge-case handling in an ordering system.

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GB

Mid-level AI/ML Engineer specializing in fraud detection and risk analytics in Financial Services

USA5y exp
JPMorgan ChaseTrine University

At JP Morgan Chase, built and deployed a production LLM-powered RAG knowledge assistant to help fraud investigators and risk analysts quickly navigate regulatory updates and internal policies, reducing investigation delays and compliance risk. Strong focus on secure retrieval (RBAC filtering), reliability (layered testing + observability), and production constraints (latency/SLOs), with Airflow-orchestrated, auditable ML pipelines.

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NP

Nikita Prasad

Screened

Mid-level AI/ML Engineer specializing in NLP, MLOps, and scalable data pipelines

Remote, USA5y exp
JPMorgan ChaseUniversity of Dayton

Built and shipped a production LLM-powered personalized client engagement assistant in the financial domain, balancing real-time recommendations with strict privacy/compliance requirements. Demonstrates strong MLOps/LLMOps depth (Airflow + MLflow, containerized microservices, drift monitoring) and a privacy-by-design approach validated in collaboration with risk and compliance teams.

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LS

Mid-level Software Engineer specializing in cloud-native microservices and workflow automation

TX, USA5y exp
ServiceNowCalifornia State University, Long Beach

Enterprise platform engineer/product owner who led end-to-end delivery of customer-facing ServiceNow Service Catalog/workflow solutions, emphasizing reliability, security, and fast iteration. Built React/TypeScript portals with Node.js and Spring Boot backends, and improved microservices reliability at scale using Kafka, monitoring, and robust retry/timeout patterns.

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VR

Vaman Rao

Screened

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

NJ, USA5y exp
UberConcordia University Wisconsin

Backend engineer focused on Python/FastAPI microservices, with hands-on experience deploying to AWS (EKS/ECR) via Jenkins and GitOps-style workflows using ArgoCD. Has built and stabilized real-time Kafka payment-event streaming pipelines and improved production performance under peak load through Redis caching, SQL optimization, and robust retry/DLQ patterns. Also supported phased migrations from on-prem environments to AWS with gradual traffic shifting and monitoring.

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HK

Harini Kv

Screened

Mid-level AI/ML Engineer specializing in GenAI, NLP, and MLOps

Dallas, TX7y exp
EquinixFitchburg State University

GenAI/data engineering practitioner with production experience across Equinix, Optum, and Citibank—built an Azure OpenAI (GPT-4) + LangChain document intelligence platform processing 1.5M+ docs/month and a HIPAA-compliant Airflow healthcare pipeline handling 5M+ claims/day. Also delivered a real-time fraud detection + explainability system using LightGBM and a fine-tuned T5 NLG component, improving fraud accuracy by 15%+ while partnering closely with compliance stakeholders.

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SY

Shishir Yadav

Screened

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

New York, NY3y exp
Freddie MacPurdue University

Software engineer in the mortgage/financial services domain (Freddie Mac) who builds end-to-end loan origination and credit risk capabilities using Spring Boot microservices, Angular dashboards, and data pipelines. Delivered measurable impact (30% reduction in underwriting turnaround time) and emphasizes production reliability/compliance with strong guardrails, observability, and evaluation loops for risk scoring systems.

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RT

Mid-level Full-Stack Software Engineer specializing in Java/Spring microservices and React

Mobile, AL4y exp
UberLindsey Wilson College

Uber engineer who has owned internal products end-to-end across backend (Spring Boot microservices, MySQL) and frontend (React), including performance optimization and secure JWT-based auth. Also shipped a production internal RAG/embeddings LLM support assistant over policy docs and support tickets, with guardrails (confidence thresholds, human review) and an evaluation loop that directly reduced hallucinations.

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SM

Sahithi M

Screened

Mid-level GenAI/ML Engineer specializing in LLM applications and enterprise automation

5y exp
UnitedHealth GroupRivier University

Built and shipped a production LLM-powered healthcare support agent at UnitedHealthGroup, using LangChain + FAISS RAG on AWS SageMaker with CloudWatch monitoring and human-in-the-loop fallbacks for safety. Strong focus on reliability engineering (confidence gating, retries/timeouts, caching) and continuous evaluation loops; reported ~40% improvement in query resolution efficiency while reducing manual support workload.

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Evan Z - Junior Software Engineer specializing in video streaming and processing systems in Champaign, IL

Evan Z

Screened

Junior Software Engineer specializing in video streaming and processing systems

Champaign, IL1y exp
PhrazeUniversity of Illinois Urbana-Champaign

Software engineering intern at China Telecom who built and continuously evolved a real-time transaction platform ("Smart Tangerine") focused on strong consistency and peak-hour concurrency. Implemented microservices with Redis and RabbitMQ to decouple heavy processing and cut latency (~80ms to ~30ms), and led a zero-downtime migration from a monolith using strangler pattern, dual-write, and traffic shadowing.

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Ganesh Bandi - Mid-level AI Engineer specializing in LLMs, RAG, and MLOps in USA

Ganesh Bandi

Screened

Mid-level AI Engineer specializing in LLMs, RAG, and MLOps

USA6y exp
Capital OneUniversity of North Texas

LLM engineer who has deployed production RAG systems for regulated document QA (PDFs/knowledge bases), emphasizing grounded answers with citations, RBAC, monitoring, and continuous feedback. Demonstrates deep practical expertise in retrieval quality (semantic chunking, hybrid BM25+embeddings, re-ranking), reliability (guardrails, deterministic workflows), and measurable evaluation (golden sets, log replay, A/B tests) while partnering closely with compliance/operations stakeholders.

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Satwik Alla - Mid-level Full-Stack Software Engineer specializing in scalable APIs and real-time AI apps in United States of America

Satwik Alla

Screened

Mid-level Full-Stack Software Engineer specializing in scalable APIs and real-time AI apps

United States of America3y exp
Cosmo AGI, LLCUniversity of Maryland, Baltimore County

Lead software engineer (3+ years) who built and scaled an AI product backend at Cosmo AGI from the ground up using FastAPI/Postgres/Redis/vector DB, targeting sub-200ms latency and supporting 1000+ active users. Strong in production-grade security and observability (OAuth/JWT, RBAC, Postgres RLS, Prometheus/Sentry), plus DevOps automation (Docker, GitHub Actions, blue-green deploys) with measurable impact on uptime, incidents, engagement, and deployment speed.

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John Hoffman - Senior Data Engineer specializing in Databricks, Spark, and AWS for government healthcare data systems in Windsor Mill, MD

John Hoffman

Screened

Senior Data Engineer specializing in Databricks, Spark, and AWS for government healthcare data systems

Windsor Mill, MD12y exp
GDITUniversity of Virginia

Python/AWS engineer focused on batch-processing and data workflows, including building reusable S3/boto3 utilities with reliability features and IAM-based auth. Has led low-risk legacy modernizations using parity testing plus a month of parallel production runs, and has owned production issues end-to-end (including fixing a client-side Excel macro) while contributing to significant AWS cost reductions (~$10k/month).

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MD

Intern Full-Stack Software Engineer specializing in web, mobile, and accessibility

Los Angeles, CA0y exp
Lumina Health InstituteUSC

Full-stack engineer who has built and shipped production Next.js (App Router + TypeScript) applications end-to-end, including an authenticated dashboard with protected routing and post-deploy troubleshooting. Designed Postgres schemas for collaboration/analytics (users/workspaces/sessions/events) and achieved ~60% query-time reduction through indexing and query-plan-driven optimization, with a strong emphasis on accessibility and server-first React architecture.

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TS

Mid-Level Full-Stack .NET Developer specializing in cloud microservices and data pipelines

6y exp
Elevance HealthMissouri State University

Backend/data engineer with experience at Citi and Elevance Health, building end-to-end pipelines and data services in regulated, high-volume environments. They combine Python, SQL, .NET, Azure Functions, and strong observability/reliability patterns to improve processing speed, reduce manual effort, and maintain high uptime across financial and healthcare data platforms.

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DM

Mid Software Engineer specializing in distributed cloud-native backend systems

Gainesville, FL4y exp
Silicon AssuranceUniversity of Florida

Backend/AI workflow engineer who built production-grade orchestration systems for hardware security verification at Silicon Assurance (Nextflow/Python/Postgres) and a multi-agent LLM-driven regulatory code checking system at the University of Florida. Emphasizes reliability: strict plan/execute/verify boundaries, queue-based isolation, and strong observability/auditability with Prometheus/Grafana and persisted prompts/tool calls.

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Amaan Elahi - Mid-level Software Engineer specializing in backend, AI, and full-stack systems in New York, NY

Amaan Elahi

Screened

Mid-level Software Engineer specializing in backend, AI, and full-stack systems

New York, NY5y exp
SAIL GTXNYU

Built and shipped production LLM agents including an internal RAG-based compliance classification system at SAIL (FastAPI/Redis/Docker) designed to handle real failure modes and scale to ~10k LLM calls/hour, achieving ~93% pipeline accuracy with reduced hallucination risk via multi-model orchestration and strict grounding. Also architected “Elara,” a state-machine-driven conversational appointment booking agent using structured JSON outputs and backend function execution for reliability, and has experience normalizing messy OTA/PMS data at RateGain.

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Pahuldeep Singh - Senior Full-Stack Developer specializing in scalable web platforms and automation in Remote

Senior Full-Stack Developer specializing in scalable web platforms and automation

Remote6y exp
CalianGeorgia Tech

Backend/full-stack engineer focused on TypeScript/Node.js systems, with hands-on ownership of a real-time telemetry and dashboard platform built on Kafka, Debezium, PostgreSQL, and GraphQL. Stands out for combining event-driven architecture, correctness/idempotency patterns, strong observability, multi-tenant security, and developer-friendly API design in production environments.

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AK

Mid-level Machine Learning Engineer specializing in MLOps, NLP, and production ML systems

5y exp
ComcastUniversity of Central Missouri

Backend/founding-engineer-style builder who designed and evolved a near-real-time customer churn prediction platform (FastAPI + AWS SageMaker/Lambda + Redis + MLflow) to enable real-time retention actions, reporting ~18% churn reduction. Demonstrates strong production engineering in secure API design, incremental migrations with data integrity safeguards, and robustness improvements in async pipelines (idempotency, DLQs, retry visibility).

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