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Vetted SQL Professionals

Pre-screened and vetted.

SK

SNEHA KUSUMA

Screened

Mid-level Java Full-Stack Developer specializing in banking and telecom platforms

Dallas, TX5y exp
U.S. BankUniversity of Central Missouri

Frontend-focused engineer with experience at T-Mobile and U.S. Bank who maintained a TypeScript utility library (types, tests, build pipeline, and docs) adopted by multiple teams, and improved React workflow performance by refactoring components and optimizing data fetching. Known for pragmatic cross-team support—reproducing issues quickly, shipping well-tested fixes, and managing changes carefully to avoid breaking downstream apps.

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AP

Mid-Level Full-Stack Software Engineer specializing in FinTech and Healthcare SaaS

Atlanta, GA3y exp
CheckrSan Francisco State University

Customer-facing technical professional with experience supporting LLM/agentic-style workflows and complex integrated systems (APIs, backend logic, databases). Partnered with sales/customer teams at Radix Health to onboard new clients in phased prototypes, translating non-technical requirements into technical scope and implementing core product changes to tailor the appointment-booking solution for providers.

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KP

Mid-level Data Analytics & ML Engineer specializing in NLP, LLMs, and cloud data platforms

Dallas, TX5y exp
MattelKennesaw State University

At KPMG, built and productionized a secure RAG-based LLM assistant that lets business and risk stakeholders query data warehouses in natural language, reducing dependence on data engineers for ad-hoc analysis. Demonstrates strong production rigor (Airflow orchestration, CI/CD, containerization), retrieval/embedding tuning (rechunking, semantic abstraction for structured data), and reliability controls (confidence thresholds, refusal behavior, monitoring and canary evals).

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RR

Mid-level Generative AI & Machine Learning Engineer specializing in agentic LLM systems

USA4y exp
OptumUniversity at Buffalo

Built and deployed a production agentic LLM knowledge assistant that answers complex questions over internal documents, APIs, and databases using a RAG architecture (FAISS/Pinecone) and LangChain/LangGraph orchestration. Emphasizes production-grade reliability and hallucination control through grounding, confidence thresholds, validation, retries/fallbacks, and full observability (logging/metrics/traces) with continuous evaluation and feedback loops.

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SV

Mid-level Data Scientist specializing in Generative AI, MLOps, and cloud data platforms

USA4y exp
CitiusTechArizona State University

GenAI/ML engineer (CitiusTech) who has deployed production RAG systems for compliance/operations document Q&A, using Pinecone + FastAPI microservices on Kubernetes with strong monitoring and guardrails. Also built a GenAI-powered incident triage/routing solution in collaboration with non-technical stakeholders, achieving 35% faster response times and 40% fewer misclassified tickets, and has hands-on orchestration experience with Airflow and AutoSys.

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IK

Ivan Kadyka

Screened

Staff Technical Lead specializing in Unity and .NET

Warsaw, Poland11y exp
TIMETOBOOKBelarusian National Technical University

Unity/gameplay engineer (Playtika) who built a state-machine/ECS-driven slot/bonus engine in a client-server setup, focusing on consistent outcomes under latency and highly engaging reward sequences. Also implemented server-authoritative real-time challenges/contests via an event-driven messaging system (SignalR-like) across iOS/Android/WebGL/UWP, and validates impact through retention/session/engagement analytics.

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AK

Ajay Kumar

Screened

Mid-Level Java Full-Stack Developer specializing in Financial Services and Healthcare IT

6y exp
VanguardLewis University

Full-stack engineer with experience at Vanguard, PNC, and Humana building customer-facing investment/banking flows and internal ops tools using Angular/React/TypeScript with Spring Boot microservices. Strong in shipping time-sensitive changes safely via automated testing/CI (JUnit/Mockito, Jenkins, SonarQube) and in operating event-driven microservices with Kafka (idempotency, retries, correlation IDs). Improved internal tool adoption by responding to ops/support feedback with query optimization and clearer search results.

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BW

Buyun Wang

Screened

Senior Full-Stack Developer specializing in web and mobile products

Vancouver, BC7y exp
HoneyBadger BitcoinUniversity of British Columbia

Frontend engineer focused on marketing and analytics products, including a real-time multi-touch attribution dashboard. Uses Next.js (SSR/ISR) with React/TypeScript and Tailwind, and emphasizes quality at scale via automated testing, CI/CD (GitHub Actions), feature-flagged staged rollouts, and Mixpanel-driven iteration. Experienced modern state management patterns (React Query + Zustand) and performance tuning (code-splitting, dynamic imports, lazy loading).

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HL

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

Bay Area, CA6y exp
Inertia SystemsPurdue University

At Inertia Systems, built a production LLM-powered ingestion pipeline that converts heterogeneous sources (PDF/JSON/IFC/SQL and financial tables) into standardized text and uses GraphRAG to construct a knowledge graph with verified dependency relationships. Also has hands-on HPC orchestration experience with SLURM, including creating a custom wrapper process manager to improve resource utilization under restrictive scheduling policies.

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MK

Manasa Konda

Screened

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

Bentonville, AR4y exp
WalmartUniversity of Central Missouri

Software engineer with experience at Walmart and Amex building customer-facing backend services and microservices at scale (RabbitMQ). Built an internal developer tooling platform integrating Figma with GitHub Copilot to automate consistent React component creation, adopted across multiple teams; emphasizes fast, safe iteration using metrics, feature flags, gradual rollouts, and automated testing.

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MB

Manav Bhasin

Screened

Junior Full-Stack Machine Learning Engineer specializing in production ML systems

San Jose, CA2y exp
AgroFocal Technologies IncSan José State University

Software engineer who owned end-to-end delivery of customer-facing agricultural forecast reporting (crop yield/health) and iterated quickly via rigorous edge-case testing and customer feedback. Also built an internal ML training platform (TypeScript/React + Flask/Python + MongoDB) used by every developer, with architecture designed to stay responsive under heavy compute load.

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SK

Mid-level Data Scientist / ML Engineer specializing in streaming ML systems for healthcare and IoT

Urbandale, IA4y exp
John DeereAuburn University at Montgomery

ML/GenAI engineer with production experience building an LLM-powered governance layer that summarizes verified drift/performance signals into validation reports and release notes, designed for regulated environments with de-identification and non-blocking fallbacks. Strong Airflow-based orchestration background across healthcare and finance, integrating Databricks/Spark and MLflow for scalable retraining/monitoring. Demonstrated ability to partner with non-technical healthcare operations teams to deliver actionable risk-scoring outputs via dashboards and automated reporting.

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AD

Ajay Desai

Screened

Mid-Level Full-Stack Software Engineer specializing in FinTech and platform APIs

USA5y exp
JPMorgan ChaseSyracuse University

Backend/AI engineer with experience in both high-scale financial services (JP Morgan trade compliance analytics API on Java/Spring Boot/Postgres/Elasticsearch on AWS EKS processing 1M+ trades/day) and applied LLM systems for legal research (LangChain/OpenAI + Weaviate semantic search). Demonstrated strength in reliability/performance engineering, data consistency during migrations, and production-grade workflow orchestration with observability and human-in-the-loop guardrails.

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JK

JiHeon Kim

Screened

Mid-Level Backend Software Engineer specializing in Financial Services

Toronto, Canada4y exp
Bank of AmericaUniversity of Alberta

Frontend engineer focused on React/TypeScript dashboards and end-to-end product delivery, including RBAC with JWT, Redux-based session persistence, and a centralized API layer with token injection. Has experience with real-time MongoDB-backed updates (shared across web and mobile) and has solved production-impacting issues like timezone inconsistencies using date-fns/UTC conversions, backed by Jest + manual QA and rollback-driven release practices.

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MM

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

Jersey City, NJ5y exp
BlackRockPace University

Backend engineer focused on high-throughput Python/Flask systems on AWS, with strong scaling and performance tuning experience (e.g., PostgreSQL join reduced from ~3s to <200ms; background aggregation cut from 10 minutes to <90 seconds with 8x throughput). Has also integrated ML model serving into production APIs (churn prediction) using Celery/Redis batching and AWS Lambda/S3, and designed secure multi-tenant architectures with PostgreSQL schema isolation and row-level security.

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OM

Owen Marcione

Screened

Intern Software Engineer specializing in embedded systems and full-stack AWS/React apps

1y exp
California Cybersecurity InstituteCal Poly San Luis Obispo

Robotics software developer building an ESP32/FreeRTOS wheel-encoder driver for a differential-drive robot with PID velocity control and ROS2 odometry publishing. Has implemented vision-based human tracking (DepthAI) and an obstacle map + EKF sensor fusion using IMU and LiDAR, with a simulation-first debugging workflow (Gazebo, Foxglove) and Dockerized environments; plans to extend to Nav2 + SLAM Toolbox for building-scale mapping.

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RR

Mid-level Data Scientist & Machine Learning Engineer specializing in fraud and forecasting

USA5y exp
JPMorgan ChaseUniversity of Texas at Dallas

ML/LLM practitioner who has shipped production RAG systems (summarization + Q&A) and end-to-end Airflow-orchestrated demand forecasting pipelines at NEON IT. Strong focus on reliability—uses evaluation scripts, retrieval/chunking tuning, validation/retries/alerts, and stakeholder-driven iteration to make AI workflows consistent and usable.

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SK

Sai Kondapaka

Screened

Mid-Level Software Engineer specializing in microservices, data pipelines, and FinTech fraud detection

Remote, USA5y exp
PayPalCalifornia State University

Backend engineer with PayPal experience owning a high-throughput, low-latency fraud detection pipeline processing billions of transactions/day, integrating LLM-based models into real-time Kafka streams and payment decisioning APIs. Strong Kubernetes + GitOps practitioner (declarative, auditable deployments; autoscaling/probe tuning) with migration experience modernizing legacy systems onto AKS/OpenShift.

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JK

Jiyun Kim

Screened

Intern Full-Stack & ML Engineer specializing in AI products and data-driven optimization

San Diego, CA2y exp
ASMLMinerva University

Worked in a startup building an automated carbon accounting/climate reporting product, partnering with client IT and internal cross-functional teams to ship features and train end users. Also has software engineering internship experience debugging complex multi-workflow systems, including uncovering a significant (~20%) data annotation error by instrumenting and testing each workflow step.

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SK

Sumit Kothari

Screened

Junior AI/Full-Stack Engineer specializing in LLM apps and RAG systems

Los Angeles, CA1y exp
Sumeru IncUSC

AI engineer who built and shipped a production AI document-understanding/search system at Sumeru Inc, including a full RAG + LLMOps evaluation stack (MLflow, DeepEval, RAGAS) deployed on GCP. Also developed LangChain/LangGraph multi-agent workflows for UAV flight-log analysis and has experience presenting AI solutions to non-technical stakeholders and prospect clients to drive POCs.

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FA

Fnu Arsh

Screened

Intern UX/UI Designer specializing in product design and data-driven UX research

Tempe, AZ1y exp
RelaytoArizona State University

Design engineer blending UX/product design with hands-on technical implementation and analytics. Built a full-stack restaurant web app (Node.js/MongoDB) and improved conversion via instrumentation (sensors/heatmaps) and UX changes; also designed a smart-meter anomaly triage dashboard using Python + Power BI to make complex data usable for non-analysts. Led trust-focused conversational UI direction for an AZ water chatbot based on deep user interviews.

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IK

Junior ML Engineer specializing in energy forecasting and battery optimization

San Carlos, CA3y exp
ElecricFishUniversity of Michigan

Backend/ML engineer working on a battery energy storage system operations dashboard: built a Flask backend integrated with OAuth and a separate FastAPI optimization/simulation service, deployed via Docker CI/CD to Azure Container Apps. Strong in productionizing ML (AzureML to batch endpoints) and in performance/scalability patterns (Postgres indexing/JSONB, per-unit data isolation, async throttling + caching for year-long CPU-intensive simulations across 40+ scenarios).

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NP

Neha P

Screened

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

Texas, State4y exp
Bank of AmericaUniversity of Central Missouri

Full-stack engineer with Bank of America experience modernizing a large-scale financial reporting platform. Built React frontends and Java/Spring Boot microservice APIs end-to-end, optimized data-heavy SQL performance (indexing/caching/pagination), and implemented an AI feature for forecasting and anomaly detection using Python/scikit-learn, with deployments supported on AWS.

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