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Vetted Indexing Professionals

Pre-screened and vetted.

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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VK

Vishnu Kumar

Screened

Mid-level Full-Stack Developer specializing in FinTech and real-time payments

Remote, USA6y exp
VenmoUniversity of North Texas

Software engineer with deep experience in real-time payments and event-driven microservices. Built a React/TypeScript + Spring Boot system using RabbitMQ, and created an internal operations dashboard that improved visibility into message-processing workflows for engineering, support, and SRE. Strong in experimentation-driven product iteration (feature flags/A-B tests) and in scaling reliability via idempotent consumers and end-to-end observability.

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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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CM

Mid-level Full-Stack Java Developer specializing in payments and event-driven microservices

Arlington, VA5y exp
IntuitGeorge Washington University

Full-stack engineer (backend-led) with recent experience building enterprise workflow orchestration and billing/payment platforms at Intuit using Java/Spring Boot (WebFlux), Kafka, Postgres/Redis, and React/TypeScript. Has operated at high scale (reported ~1200 RPS during month-end billing) and focuses on event-driven microservices, real-time UI updates via streaming, and disciplined API evolution with contract testing.

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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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RA

Mid-Level Software Engineer specializing in Payments and Financial Services

United States5y exp
JPMorgan ChaseUniversity of North Texas

Software engineer with hands-on experience improving performance and reliability in financial workflows (settlements/loan processing), spanning React/TypeScript and Angular frontends plus Spring Boot microservices. Has delivered measurable latency improvements using PostgreSQL optimization and Redis caching, and has operated Kafka-based systems at scale with idempotent processing and backoff/retry strategies while iterating internal ops tooling with support/finance teams.

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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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KL

Krishna Lella

Screened

Mid-level Full-Stack Developer specializing in FinTech platforms

New York, NY4y exp
PayPalSt. Francis College

Product-focused full-stack engineer who built and shipped subscription/billing features end-to-end (FastAPI + React/TypeScript), including a self-serve cancellation flow with save-offers that reduced support tickets and improved churn insights. Experienced operating on AWS (ECS/EC2, RDS, S3/CloudFront) and handling real production scaling incidents through DB/query optimization, idempotent API design, and strong observability practices.

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VP

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

United States6y exp
State FarmMurray State University

Full-stack engineer with production ownership across React/TypeScript, Node/Express, and Postgres, including zero-downtime releases and rollbackable migrations. Demonstrated measurable performance wins (20% response-time reduction) through DB query profiling and batching, plus hands-on AWS operations (ECS/Lambda/CloudWatch) and reliability patterns for ETL (retries, DLQs, idempotency). Experience shipping microservices quickly in ambiguous, fast-paced environments (Deloitte).

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RR

Mid-level Full-Stack Developer specializing in cloud-native microservices and event-driven systems

4y exp
Molina HealthcareUniversity at Buffalo

Software engineer with experience at Molina Healthcare and Target, owning production features end-to-end across backend, data pipelines, and UI. Built an event-driven claims validation system (Python/Java/Spring Boot/Kafka) with strong observability, and shipped embeddings-based semantic product search with evaluation loops (CTR/top-k + human review) and guardrails like keyword-search fallback.

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BR

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

Sunnyvale, CA5y exp
WalmartArizona State University

Backend/platform engineer who has built and run production Python/Flask + Kafka microservices processing RFID and camera/RFID fusion streams for near-real-time retail cart updates at ~4–5M events/day. Strong in reliability/performance debugging (p99 latency, Kafka lag, Cosmos DB RU hot partitions) with measurable impact including ~30% database cost reduction, and has also shipped an end-to-end vulnerability scanning workflow with DynamoDB-backed state, idempotency, and robust retry/verification guardrails.

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PC

Pranav Chand

Screened

Senior AI/ML Engineer specializing in Generative AI and LLM platforms

ServiceNow, CA5y exp
ServiceNowCalifornia State University, Fullerton

Backend engineer focused on multi-tenant enterprise AI personalization and recommendation platforms, combining ML/LLM intent extraction with deterministic policy guardrails for compliance and auditability. Has hands-on AWS experience (ECS/Lambda/DynamoDB/S3) and led a careful DynamoDB single-table migration using dual write/read, canary + feature-flag rollouts, and strong observability/security (JWT/OAuth2, RBAC, Postgres RLS).

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SR

SAI RAKAM

Screened

Mid-Level Software Engineer specializing in backend microservices and FinTech payments

Remote, USA3y exp
Capital OneGeorge Mason University

Capital One engineer focused on fraud and payments platforms, owning end-to-end services and internal tools used by fraud analysts. Built high-traffic Kafka/REST systems and real-time React/TypeScript dashboards (WebSockets, Redis), with strong emphasis on observability, idempotency, and scalable microservices. Successfully drove adoption of AI-assisted fraud classification by pairing transparency and manual overrides with measurable workflow improvements.

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KF

Kevin Fang

Screened

Intern Software Engineer specializing in full-stack and data systems

Beverly Hills, CA1y exp
Alo YogaUC Irvine

Software developer with healthcare operations experience at Epic Systems (Referrals & Authorizations), delivering customer-facing tooling to speed manual insurance authorization/denial documentation and support future automation. Also supported an HRIS migration to Workday at Aloe Yoga, solving legacy ID interoperability via scripting and mapping, and demonstrates strong production debugging and test-driven maintainability practices.

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SV

Mid-level AI/ML Engineer specializing in Generative AI and Conversational AI

Remote5y exp
InfosysUniversity at Buffalo

GenAI Engineer at Infosys who built and deployed a production multi-agent RAG system for a top-tier bank, scaling to ~50,000 queries/day with 99.9% uptime. Drove measurable gains (45% accuracy improvement, 30% API cost reduction) through open-source LLM fine-tuning, Pinecone indexing/retrieval optimization, and AWS-based MLOps/monitoring, and has experience enabling adoption via developer workshops and customer-facing collaboration.

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NM

Mid-level Frontend Software Engineer specializing in React, Next.js, and TypeScript

Dallas – Fort Worth, TX4y exp
FedExUniversity of Texas at Arlington

Product-focused full-stack engineer with FedEx experience building an internal logistics dashboard for near real-time shipment status and performance metrics using Next.js App Router + TypeScript. Strong in production ownership and performance work—uses React Profiler/Chrome DevTools to eliminate expensive re-renders and applies Postgres indexing/query tuning validated via EXPLAIN ANALYZE to improve dashboard responsiveness.

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SK

Mid-level Full-Stack Developer specializing in FinTech and enterprise web platforms

USA4y exp
JPMorgan ChaseChristian Brothers University

Software engineer with JPMorgan Chase experience building production real-time dashboards for financial risk metrics. Strong full-stack background (React/TypeScript + Node/Express + PostgreSQL) and production operations on AWS (ECS, CloudWatch) with CI/CD and observability tooling; has optimized ingestion and query performance for millions of trading-log records.

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IS

Irfan Shaik

Screened

Mid-level AI Software Engineer specializing in risk and fraud detection

Los Angeles, California4y exp
VisaGeorge Mason University

AI/software engineer with experience at Visa building a real-time transaction fraud/risk scoring microservice in the card authorization path (Python, Kafka, Kubernetes on AWS) with strict 120–150ms latency constraints and reason-code outputs for downstream decisioning. Owns ML backend end-to-end (data/feature engineering, model training, deployment) and has demonstrated production reliability work including latency spike mitigation, SLO-based observability, drift monitoring, and safe fallbacks to rule-based decisions.

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RH

Rahul Hatkar

Screened

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

San Francisco, CA6y exp
Scale AIWebster University

AI/ML engineer who has shipped production AI systems end-to-end, including an automated multi-channel (Gmail/WhatsApp/voice) candidate interviewing workflow and an enterprise RAG knowledge search platform. Demonstrates strong production rigor (monitoring, A/B tests, guardrails, schema validation, shadow testing) with quantified impact: ~60–70% reduction in interview evaluation time and ~20–30% relevance gains in RAG retrieval.

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AJ

Intern Software Engineer specializing in cloud, DevOps, and applied AI

Carlsbad, CA1y exp
ViasatUSC

Full-stack engineer with startup ownership experience (Aiir) building 15+ TypeScript/Go microservice APIs on GCP Cloud Run with Kafka-based async event streaming and React CRM integrations for billing/analytics. Strong post-launch operator who tuned Oracle performance (partitioning/indexing/query optimization) and validated a 23% retrieval-time reduction via AWR, and has a quality/DevSecOps mindset (94% Pytest coverage, GitHub Actions, SonarQube, Twistlock, CloudWatch) including migrating 18+ production CI/CD pipelines.

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SM

Mid-Level Software Developer specializing in backend, cloud, and GenAI

CA, USA5y exp
Azul ArcCalifornia State University

Full-stack engineer with fintech and AI feature experience who shipped an AI-powered project summary module in Next.js (App Router + TypeScript) with secure server-side fetching and route handlers to a FastAPI backend, then owned monitoring and performance fixes in production. Demonstrated measurable UX wins (30% faster dashboard loads) and strong backend fundamentals (Postgres indexing/EXPLAIN ANALYZE, SQS-orchestrated idempotent reconciliation workflows with DLQs and retries).

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RA

Ravali Aleti

Screened

Senior Python Developer specializing in AWS backend APIs and enterprise authentication

Philadelphia, US7y exp
ComcastUniversity of Bridgeport

Backend/data engineer focused on AWS-based Python services and data pipelines: built a Django/DRF user management/auth platform deployed with serverless AWS (Lambda/API Gateway) and event-driven workflows (Step Functions/EventBridge), with CloudFormation + Jenkins for automated delivery and Secrets Manager/Parameter Store for secure config. Also delivered AWS Glue ETL from S3 to RDS with schema evolution controls and incident-driven improvements, and has demonstrated measurable SQL tuning impact (minutes-to-seconds).

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AN

Akhil Nakka

Screened

Mid-level Software Developer specializing in FinTech microservices and cloud-native systems

Remote, USA4y exp
JPMorgan ChaseGeorge Mason University

Full Stack Engineer in fintech (JPMorgan) who owns products end-to-end across React UIs and Spring Boot/Kafka backends, with a strong track record of shipping quickly while maintaining reliability via testing, monitoring, and feature flags. Has hands-on experience scaling microservices for high-volume transactions and debugging production latency using ELK/CloudWatch, plus built an internal Python/Flask automation tool adopted by backend engineers to speed API validation and debugging.

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VS

Junior Software Engineer specializing in distributed systems and full-stack web development

Ithaca, NY2y exp
CimpressCornell University

Software engineer at Cimpress owning end-to-end transactional pages for Pens.com (e-commerce). Built and integrated new discount experiences in a React/TypeScript + Node.js stack, focusing on modular component architecture to reduce tight coupling and avoid breaking existing functionality; prioritizes roadmap work using performance and conversion metrics.

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