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Vetted NoSQL Professionals

Pre-screened and vetted.

BD

Mid-Level Software Engineer specializing in FinTech and Healthcare platforms

Remote, USA4y exp
BNY MellonUniversity at Albany

Full-stack engineer with strong data/regulatory reporting background (BNY) who owns customer-facing and internal reporting products end-to-end—from ETL/SQL transformations through React/TypeScript UIs and Spring Boot APIs. Built role-based, audit-friendly dashboards and designed RabbitMQ-based event-driven microservices with reliability patterns (idempotent consumers, publisher confirms, Saga) to scale workflows across teams.

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VR

Mid-Level Software Engineer specializing in Java/Spring microservices and event-driven systems

Kansas City, MO5y exp
Wells FargoUniversity of Missouri-Kansas City

Software engineer experienced in e-commerce systems, building customer-facing features and internal operations tools with TypeScript/React frontends and Spring Boot microservices. Demonstrated measurable performance wins (order-tracking API improved from ~2s to <700ms) and strong event-driven reliability practices with RabbitMQ (idempotency, DLQs, retry/backoff), including resolving a production queue backlog incident. Built an ops dashboard with real-time cross-service order tracing that became a daily tool for support/ops and reduced escalations to engineering.

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AM

Mid-Level Software Engineer specializing in backend microservices and distributed systems

Waltham, MA4y exp
Dassault SystèmesNortheastern University

Built and productionized an internal LLM-powered search tool that helps engineers find the right SolidWorks macros using plain-English queries, using OpenAI embeddings and ChromaDB with strong logging/fallback safeguards. Experienced in diagnosing RAG/agentic workflow issues in real time and in hands-on API support, including fixing customer macros after SolidWorks version updates and driving adoption through reusable solutions and best practices.

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LV

Mid-Level Software Developer specializing in Java/Spring microservices and Salesforce

USA5y exp
Wells FargoUniversity of Maryland, Baltimore County

Backend/AI engineer who built an AI icon-generation SaaS backend (Java/Spring Boot, MongoDB) on AWS, including async job processing with idempotency and S3-based result storage to handle traffic spikes. Also shipped applied AI in finance—an end-to-end fraud detection pipeline with risk scoring—and designed a banking support AI agent with strict guardrails, audit logs, and human-in-the-loop escalation.

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SS

Swetha Sai

Screened

Mid-Level Software Engineer specializing in cloud-native microservices and analytics platforms

Remote, USA4y exp
Bank of AmericaUniversity of Maryland, Baltimore County

JavaScript engineer with a track record of diagnosing and fixing real performance issues end-to-end—profiled a charting library freeze on large datasets, rewrote layout logic to batch updates, added tests, and got the PR merged upstream. Also has experience stabilizing backend services in ambiguous, fast-moving projects by defining priorities, tightening API contracts, and owning delivery through deployment.

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MB

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

Strongsville, Ohio5y exp
PNCUniversity of Dayton

Full-stack engineer focused on modernizing legacy financial/compliance platforms into cloud-native, domain-driven microservices. Deep hands-on experience across Spring Boot/Kafka/Redis/Postgres-Mongo backends and React/Angular frontends, with strong CI/CD and Kubernetes/OpenShift deployment practices for real-time, high-volume workloads.

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HE

Mid-level AI/ML Engineer specializing in cloud data engineering and GenAI

Florida, USA6y exp
LexisNexisUniversity of South Florida

AI/LLM engineer with production experience in legal tech: built a GPT-4 + LangChain RAG summarization system at Govpanel that reduced legal case-file review time by 50%+. Previously at LexisNexis, orchestrated end-to-end Airflow data/AI pipelines processing 5M+ legal documents daily, improving ETL runtime by 35% with robust validation, monitoring, and SLAs.

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SK

Shiva Kumar

Screened

Mid-Level Full-Stack Developer specializing in Java/Spring Boot and React in banking

Chicago, IL4y exp
CitigroupGovernors State University

Full-stack engineer (4+ years) with Citigroup experience building a modular banking dashboard using React/TypeScript/Redux and a Java Spring Boot microservices backend (12+ services) integrated with Kafka. Strong in reliability/observability and cloud operations on AWS (EC2/S3/Lambda, CloudWatch, Prometheus, ELK, IaC with Terraform/CloudFormation), with quantified improvements in latency, development speed, and data pipeline correctness.

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CT

Mid-level AI/ML Engineer specializing in LLM systems, RAG, and MLOps

5y exp
HCA HealthcareUniversity of South Florida

Built a production, real-time clinical documentation system at HCA that converts doctor–patient conversations into structured clinical summaries using speech-to-text, LLM summarization, and RAG. Demonstrated measurable gains from medical-domain fine-tuning (clinical concept recall +18%, ROUGE-L 0.62 to 0.74) while meeting HIPAA constraints via PHI anonymization and encryption, and deployed via Docker/FastAPI with CI/CD and monitoring.

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AC

Mid-Level Full-Stack Software Engineer specializing in hybrid cloud platforms

San Jose, CA3y exp
HPEUniversity of Windsor

Full-stack engineer from HPE GreenLake who built and owned a cloud/hypervisor resource management experience end-to-end, including Postgres modeling, typed REST/GraphQL integrations, and resilient provisioning workflows. Drove a centralized Redux-based UI architecture that boosted dev velocity by 50% across 30+ teams, and continued post-launch ownership with DR integrations (AWS/GCP/Azure) plus expanded Cypress testing and observability.

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VM

Mid-Level Full-Stack/Backend Engineer specializing in AWS, APIs, and GenAI systems

Los Angeles, CA5y exp
AIRKITCHENZCalifornia State University, Fullerton

Backend engineer who built the core backend for Air Kitchens’ discovery/booking platform on AWS (Node + Python, DynamoDB, SQS/Lambda), optimizing for fast user-facing APIs and scalable async workflows. Introduced an AI matching service with a deterministic pre-filter + LLM ranking approach to balance latency vs quality, and has hands-on experience with production security (JWT/RBAC/RLS), CI/CD, and blue-green, staged migrations from Django to modular services.

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AT

Intern Data Scientist specializing in ML engineering and LLM agentic workflows

San Francisco, CA6y exp
ContentstackSan José State University

Built an agentic, multi-step LLM system that generates full-stack code for API integrations using LangChain orchestration, Pinecone/SentenceBERT RAG, and a human-in-the-loop feedback loop for iterative code refinement. Also collaborated with non-technical content writers and PMs during a Contentstack internship to deliver a Slack-based AI workflow that generates and brand-checks articles with one-click approvals.

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ST

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

Minneapolis, MN5y exp
Wells FargoConcordia University

Full-stack engineer with experience at Wells Fargo and Salesforce building regulated, customer-facing financial systems and internal DevOps tooling. Deep in microservices and event-driven architectures (Spring Boot, Kafka/RabbitMQ) with strong CI/CD automation, contract testing, and observability; delivered measurable impact including 60% faster deployments and 40% fewer support tickets.

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UK

Mid-Level Full-Stack Java Engineer specializing in microservices and cloud platforms

Austin, Texas5y exp
CenteneWebster University

Frontend/platform-leaning engineer who owned a shared React component library (design-system style) adopted across multiple SPAs, with strong discipline around SemVer, deprecation strategy, and developer documentation. Also has backend/distributed-systems experience diagnosing and fixing a Kafka microservice race condition and has led prioritization/migration planning in an unstructured monolith-to-microservices environment (Centene).

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RN

Mid-level Full-Stack Software Engineer specializing in cloud-native microservices

4y exp
American ExpressUniversity of North Texas

Full-stack engineer who owned end-to-end delivery of a customer-facing financial services web platform and built internal tooling for engineering teams. Strong in microservices and event-driven systems (Kafka/RabbitMQ), distributed transaction management (saga), and production performance/observability—achieving ~40% backend response-time improvement through database and query optimization.

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SM

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

WI, USA3y exp
Cardinal HealthAnderson University

Full-stack engineer with enterprise experience at Metasystems Inc. (and Qualcomm) building high-traffic, security-sensitive systems—owned a secure transaction processing module end-to-end using Java/Spring Boot, Python/Django, and React. Strong AWS production operations (EKS/ECS/Lambda/RDS/DynamoDB) with IaC (Terraform/CloudFormation), observability, and reliability patterns; also delivered resilient ETL/integration pipelines with idempotency/retries/backfills and achieved a 50% deployment-time reduction through CI/CD and modular refactoring.

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HS

Harsha Sikha

Screened

Mid-level AI/ML Engineer specializing in Generative AI and data engineering

Armonk, New York4y exp
IBMSaint Peter's University

IBM engineer who built and deployed a production RAG-based LLM assistant using LangChain/FAISS with a fine-tuned LLaMA model, served via FastAPI microservices on Kubernetes, achieving 99%+ uptime. Demonstrates strong practical expertise in reducing hallucinations (semantic chunking + metadata-driven retrieval) and managing latency, plus mature MLOps practices (Airflow/dbt pipelines, MLflow tracking, monitoring, A/B and shadow deployments) and effective collaboration with non-technical stakeholders.

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BP

Bhakti Patel

Screened

Senior Full-Stack Software Engineer specializing in .NET, Python, and cloud-native systems

Worcester, MA11y exp
Worcester Polytechnic InstituteWorcester Polytechnic Institute

Full-stack engineer who owned an end-to-end production feature for a Piraeus Bank stock exchange module, spanning React/TypeScript, backend services, and cloud operations with Docker + CI/CD, delivering reported 90% faster API responses and improved uptime. Also built a Smartwound research MVP on AWS, creating a Python image-processing/scoring pipeline to ship despite unclear image-analysis specs.

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SP

shravya potu

Screened

Mid-Level Full-Stack Software Engineer specializing in cloud-native microservices

6y exp
Capital OneUniversity of North Texas

Full-stack engineer with experience at Capital One and Prime Softech owning production systems end-to-end: secure authentication (Java/Spring Security + React/Redux) through AWS ECS deployments with Terraform and CI/CD. Strong reliability/observability focus (Prometheus/Grafana/ELK/CloudWatch) with quantified improvements (15% reliability gain, 30% fewer post-release defects). Also led legacy monolith-to-microservices refactors and built real-time Kafka/Spark ingestion pipelines for analytics/fraud detection.

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JS

Jafeeza Shaik

Screened

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

3y exp
Wells FargoUniversity at Buffalo

Robotics software engineer focused on multi-robot fleet orchestration in ROS 2, owning the fleet manager and task dispatch layer for pick/drop workflows. Strong in real-world reliability and safety (heartbeats, idempotent tasking, E-stop/localization confidence gates) and in debugging timing/state issues via telemetry alignment and rosbag replay, with experience in simulation, CI/CD, Docker, and Kubernetes-based deployments.

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AM

Mid-level Data Scientist specializing in LLMs, RAG, and document intelligence

NYC, NY3y exp
MagnitUniversity at Buffalo

LLM/ML engineer who has shipped production systems in legal/financial-risk domains at Wolters Kluwer, including a hybrid OCR+deterministic+LLM extraction pipeline that structured UCC filings at massive scale and drove $6M+ in revenue. Also built LangGraph-based multi-agent “Deep Research” workflows with model routing, tool calls (MCP), persistence, and human-in-the-loop review, and partnered closely with policy writers to deliver LLM summarization that cut writing time by ~60%.

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LJ

Lokesh Jain

Screened

Senior Data Engineer specializing in cloud data platforms and ML pipelines

5y exp
WayfairUniversity at Buffalo

Built and deployed AcademiQ Ai, a production LLM-based teaching assistant using GPT/BERT with RAG (LangChain + Pinecone) to handle large student notes and generate adaptive explanations/quizzes. Demonstrated measurable retrieval-quality gains (18% precision improvement, 22% less irrelevant context) by tuning similarity thresholds and chunking based on user satisfaction signals. Also orchestrated terabyte-scale, real-time demand forecasting pipelines using Airflow and Kubeflow on GCP with strong monitoring, shadow deployment, and feedback-loop practices.

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SR

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

Minneapolis, MN4y exp
UnitedHealth GroupUniversity of Memphis

Software engineer/product owner experience at UnitedHealth Group owning a high-volume claims eligibility console end-to-end (React/TypeScript + Spring Boot microservices) processing 1M+ transactions/day. Strong in event-driven architecture (Kafka/RabbitMQ), HIPAA-aligned security (OAuth/JWT/RBAC), and building internal observability tools that improve incident triage and production reliability.

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NN

Mid-Level Software Engineer specializing in data engineering and cloud platforms

Bentonville, AR3y exp
WalmartFlorida Atlantic University

Backend-leaning full-stack engineer who has shipped production-critical data/reporting features at Walmart and built an end-to-end workflow automation product (FastAPI + React/TypeScript + PostgreSQL) deployed on AWS. Strong in performance/reliability engineering (parallel ETL, batch DB operations, indexing via EXPLAIN ANALYZE), secure API design (JWT/RBAC), and pragmatic incident-driven scaling (separating workers from API layer).

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