Vetted MySQL Professionals

Pre-screened and vetted.

PC

Prateek C

Screened

Mid-Level Full-Stack Software Engineer specializing in Java/Spring, React, and AWS

San Francisco, CA6y exp
ShopifyClemson University

Backend/full-stack engineer (5+ years) with Shopify experience integrating LLM/RAG workflows into production APIs. Owned a Python TensorFlow Serving inference pipeline connected to Java microservices via gRPC, optimizing tail latency at ~10k concurrent load and improving retrieval relevance with embedding and evaluation work. Strong Kubernetes/EKS + GitOps/CI/CD background, including monolith-to-microservices migrations and event-driven streaming patterns.

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VK

Mid-level Robotics Software Engineer specializing in perception and motion planning

USA4y exp
GrayMatter RoboticsPurdue University

Robotics software engineer focused on ROS2 motion and calibration systems—built a trajectory generator/low-level controller using TOPPRA that improved robot motion speed by 11x while increasing accuracy. Experienced making high-frequency robot communication more real-time (core isolation) and shipping ROS2 modules via Docker-backed CI/CD, including serving as release manager coordinating reviews, release notes, and QA.

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RM

Rohith M

Screened

Mid-level Full-Stack Developer specializing in AWS serverless and Java/Spring

Austin, Texas6y exp
AppleUniversity of Bridgeport

Built and shipped a production generative-AI recipe feature on AWS serverless (Lambda + Bedrock), evolving it post-launch from fully AI-generated outputs to user-guided structured generation based on real usage patterns and system metrics. Emphasizes reliability via prompt constraints plus deterministic validation, with automated/human eval loops and CloudWatch-based observability to manage latency, cost, and output consistency.

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Shuju Sun - Mid-Level Software Engineer specializing in real-time data pipelines and ML deployment in PA, USA

Shuju Sun

Screened

Mid-Level Software Engineer specializing in real-time data pipelines and ML deployment

PA, USA4y exp
VanguardUSC

Ticketmaster data engineer who built CDC-driven Kafka pipelines feeding Snowflake for analytics and data science teams. Hands-on in production operations—scaled Kafka during sudden playoff-driven transaction spikes and improved monitoring for preemptive scaling. Known for using small-batch experiments and quantitative metrics to align stakeholders and drive cost-saving architecture changes (e.g., buffering to reduce AWS Lambda invocation frequency).

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VK

Vasanthi Koya

Screened

Senior Full-Stack/Data Engineer specializing in cloud data pipelines for legal and financial platforms

Schaumburg, IL6y exp
DocuSignUniversity of Illinois Springfield

Data/analytics engineer who built and operated a DocuSign-based real-time analytics platform end-to-end, processing 20–50k webhook events/day with ~99.5% reliability. Strong in idempotent event processing, schema-evolution-safe ingestion (raw JSON + dynamic parsing), and serving data via versioned, low-latency REST APIs with solid CI/CD and observability.

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AU

Junior Software Engineer specializing in identity and backend systems

Redwood City, CA3y exp
OracleGeorgia Tech

Sole engineer on a large-scale authentication migration moving 350+ tenants from password-based auth to OAuth 2.0 client credentials, delivering zero downtime, full adoption, and no support tickets. Also has early hands-on experience with agentic LLM proof-of-concepts and has built structured workflow tooling to reduce ambiguity in customer-to-engineering handoffs.

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AC

Mid-level Software Engineer specializing in full-stack development and AI

New York, NY4y exp
Okada & CompanyColumbia University

Frontend developer/designer who built an in-house real estate dashboard for Okhara & Company, owning the flow from Figma design through React implementation and production iteration. Worked in a small team environment, focused on turning complex backend outputs into usable, polished interfaces with responsive design, PWA support, and performance optimizations.

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Harsh Sanas - Junior Full-Stack Engineer specializing in AI systems and cloud applications in San Francisco, CA

Harsh Sanas

Screened

Junior Full-Stack Engineer specializing in AI systems and cloud applications

San Francisco, CA2y exp
Scale AIUSC

Full-stack engineer with a strong applied AI bent who has built both a real-time EV charging platform and a production text-to-SQL system. Particularly compelling for teams needing someone who can bridge frontend, backend, infrastructure, and LLM evaluation/safety work, with experience shipping under early-stage ambiguity and integrating software with real-world hardware.

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JY

Jiaying Yun

Screened

Junior Application Engineer specializing in AI platforms and data analytics

Atlanta, GA2y exp
BlackRockUniversity of Chicago

BlackRock application engineer/product owner focused on enterprise AI platforms, building internal GenAI and ML workflow products for operations and business teams. Stands out for combining consultative solution design with hands-on implementation, including a contract review platform that cut first-draft review time by 60%+ and an AI mailbox tool that drew interest from 17 additional teams during the POC stage.

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YY

Yuanhui Yang

Screened

Senior Software Engineer specializing in Python backend systems on AWS

Livermore, CA8y exp
ASMLShanghai Jiao Tong University

Backend/data engineer from ASML who modernized a legacy SAS-based statistical processing system into a cloud-native AWS platform (Lambda/FastAPI, Step Functions/EventBridge, Glue, S3/RDS) with strong reliability and data-quality practices. Demonstrated measurable performance wins (RDS query reduced from 90+ seconds to <5 seconds) and hands-on incident ownership for production ETL pipelines.

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SB

Sowmya Battu

Screened

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

Greater Seattle Area, WA6y exp
AmazonUniversity of Houston

Amazon experience integrating LLM-powered chat automation into Amazon Connect contact-center workflows, taking prototypes to production with compliance-minded guardrails, schema/policy validation, and robust fallbacks. Regularly supports rollout and adoption via developer workshops, integration guides, and customer calls, with strong production triage and observability practices.

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KA

Principal Enterprise Cloud Architect specializing in secure modernization and AI-ready infrastructure

Potomac, MD28y exp
Kourosh Consulting Services, LLCJohns Hopkins University

Bootstrapped founder building a cybersecurity framework for cloud-native applications and startups, differentiated by significantly faster end-to-end cloud environment delivery than traditional consulting. Has experience navigating pricing models (fixed price vs time & materials) using MVP and phased delivery, and has strong familiarity with the VC/accelerator landscape with interest in healthcare (details under NDA).

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Kaustubh Rai - Junior Software Engineer specializing in scalable distributed systems and cloud platforms in Pittsburgh, PA

Kaustubh Rai

Screened

Junior Software Engineer specializing in scalable distributed systems and cloud platforms

Pittsburgh, PA2y exp
eParts Services LLCCarnegie Mellon University

Backend engineer with experience at UnitedHealth Group redesigning a high-traffic Spring Boot microservice from blocking to reactive architecture during peak season, cutting median latency by 47% for a service used by ~10M customers annually. Strong in Kubernetes-based deployment/scaling and pragmatic rollout strategies (blue-green/incremental traffic shifting) with performance and database troubleshooting.

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KB

Kartheek B

Screened

Senior Workday HCM Consultant specializing in HRIS, payroll, and integrations

Columbus, OH9y exp
KeyBankIllinois Institute of Technology

Compensation and payroll professional with hands-on ownership of end-to-end U.S. payroll and compensation cycle support. Stands out for using compa-ratio, market benchmarking, and Excel-based reconciliation tools to catch data issues, influence salary decisions, and strengthen payroll controls.

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VG

Machine learning engineer and software developer with experience across fintech, e-commerce, and gaming.

Dallas, Texas, USA6y exp
Fidelity InvestmentsUniversity of the Cumberlands

ML/AI engineer with hands-on ownership of production systems spanning classical ML fraud detection and GenAI agent workflows. At Fidelity, they built an end-to-end fraud platform that improved review queue Precision@K by 15-20% while reducing false positives 10-15%, and they also shipped RAG-based agent systems that cut manual workflow effort by 30-40%.

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Nilesh Dixit - Executive AI engineering leader specializing in agentic AI and enterprise platforms in San Francisco, CA

Nilesh Dixit

Screened

Executive AI engineering leader specializing in agentic AI and enterprise platforms

San Francisco, CA24y exp
Zeehub AICentre for Development of Advanced Computing

Bay Area engineering leader and startup co-founder with a rare mix of deep hands-on architecture experience, large-scale people leadership, and cross-functional product ownership. He helped launch GE Digital's industrial IoT efforts, holds multiple patents in the space, has scaled teams to 60-70 people, and has led both enterprise platform modernization and AI startup product development.

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SC

Shuxuan Chen

Screened

Junior Data Analyst specializing in analytics, product insights, and FinTech

New York, NY3y exp
L&G Research and Evaluation Consulting, Inc.Columbia University

Candidate mentioned working in a GTM role at Swing Phi, supporting cross-functional efforts around customer segmentation, profiling, and sales pipeline targeting. They cited using Python, SQL, and Excel for data analysis and attributed a 5% increase in acquisition rate to this work.

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JG

Jayanth Godi

Screened

Mid-level Site Reliability Engineer specializing in cloud infrastructure, Kubernetes, and LLM applications

San Jose, CA6y exp
AmazonSan Jose State University

SRE-focused engineer with experience at Sony Interactive Entertainment productionizing high-throughput LLM/agentic systems on Kubernetes, including GPU-aware autoscaling and warm-pool strategies to manage latency and cost under traffic spikes. Demonstrates strong incident response using Prometheus/Grafana + Jaeger tracing (e.g., resolving recursive agent loops and restoring 99.9% availability within minutes) and partners closely with sales/customer teams through PoV demos and developer workshops.

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SS

Shubham Singh

Screened

Mid-level Software Engineer specializing in LLM systems and intelligent search

CO, USA6y exp
PalantirSan José State University

Backend engineer from Palantir who built and productionized an enterprise LLM-based document intelligence/search platform, evolving it into a hybrid lexical+vector retrieval system. Emphasizes reliability and cost control via strict LLM gating, robust fallback paths, and evaluation frameworks (e.g., MMLU/BLEU), plus disciplined migration practices (feature flags, dual-writes, shadow reads) to ship changes safely at scale.

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SS

Shubham Singh

Screened

Mid-level AI/ML Engineer specializing in speech, computer vision, and agentic GenAI

Pittsburgh, PA6y exp
Musing AICarnegie Mellon University

Built and shipped a production multi-agent, voice-based conversational assistant for older adults’ daily health management using Vertex AI, FastAPI, Firebase/Firestore, and Cloud Run, with a custom cross-session memory design to keep responses context-aware at low latency. Also partnered with caregivers/elderly users and health officials, translating needs into workflows and explaining HIV risk predictions with SHAP and dashboards.

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JY

Jiacheng Yin

Screened

Intern Software Engineer specializing in data engineering and AI agent systems

Beijing, China1y exp
JD.comCornell University

AI engineer at Anote.ai who built and shipped a production multi-agent LangGraph/LangChain/Ray RAG platform for enterprise search and workflow automation, supporting 3 commercial products and 100+ developers. Drove measurable gains (30% accuracy improvement, lower latency) and improved reliability with Redis-based state checkpointing, message-queue synchronization, and Milvus retrieval optimizations, while partnering with PMs/clients to add transparency features like confidence scores and real-time logs.

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Akhilaa Sonduri - Junior Full-Stack Software Engineer specializing in SaaS and AI-powered web apps in Cambridge, MA

Junior Full-Stack Software Engineer specializing in SaaS and AI-powered web apps

Cambridge, MA2y exp
HubSpotUSC

Full-stack engineer with experience at HubSpot, Accolite, and an early-stage USC alumni startup (Workup). Built and shipped end-to-end workflow automation features (dynamic input configuration with strict schema validation) driving ~25% faster configuration, and delivered an AI interview customization feature in a high-ambiguity startup setting that increased adoption by ~40%. Comfortable operating production systems on AWS with CloudWatch observability and CI/CD, and has built real-time web apps with caching/indexing for performance.

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Manjory saran - Senior Backend & Infrastructure Engineer specializing in cloud-native distributed systems

Manjory saran

Screened

Senior Backend & Infrastructure Engineer specializing in cloud-native distributed systems

5y exp
WalmartSan José State University

LLM infrastructure engineer who built a production-critical real-time personalization and memory retrieval system for a user-facing product, adding <100ms P99 latency while improving relevance ~20–25% and holding SLA through 3x traffic. Experienced designing tiered retrieval backends (Redis + vector store), deploying on Kubernetes with autoscaling/circuit breakers, and running rigorous observability, incident response, and agent evaluation (shadow traffic, A/B tests, regression/replay).

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Feras Alsaiari - Senior Software Engineer specializing in AWS data platforms and event-driven systems

Senior Software Engineer specializing in AWS data platforms and event-driven systems

4y exp
Capital OneGeorgia Tech

Capital One engineer leading the architecture and delivery of a large-scale AWS Glue/Spark/Delta Lake batch messaging pipeline that decoupled batch from real-time flows, added multi-region failover and automated retries, and delivered ~40% AWS cost savings with ~3x performance gains. Currently building an LLM-powered Slack bot using RAG to automate message investigations by querying CloudWatch, Snowflake, and internal documentation with privacy-aware masking of NPI/PII.

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