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Vetted SQL Professionals

Pre-screened and vetted.

PJ

Po Jui Lin

Screened

Mid-Level Full-Stack Engineer specializing in cloud platforms, cybersecurity web apps, and IoT

Seattle, WA3y exp
AmazonUniversity of Washington

Backend engineer with experience at Amazon building an API-driven service (APS) for large-scale prompt optimization jobs using AWS Step Functions, Batch/Fargate, DynamoDB, and S3, emphasizing idempotency, observability, and secure execution boundaries. Also led a multi-tenant enterprise policy/configuration backend refactor at MAMIT Cyber with versioned schemas, shadow writes, feature-flagged rollout, and PostgreSQL RLS-based tenant isolation.

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SL

Mid-level Machine Learning Engineer specializing in MLOps and multimodal AI

KS, USA5y exp
AppleUniversity of Central Missouri

ML/AI engineer focused on production-grade model reliability: built a monitoring and validation framework to detect drift, trigger anomaly alerts/retraining, and maintain consistent performance for device intelligence workflows at scale. Strong MLOps background with Python pipelines, Docker/Kubernetes deployments, Airflow orchestration, and real-time monitoring dashboards; experienced partnering with product managers to deliver business-facing insights.

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RB

Rojin Bakhti

Screened

Junior Software Engineer specializing in Edge AI and ML deployment

San Diego, CA3y exp
QualcommUSC

Qualcomm engineer building Android applications that run on Qualcomm AI accelerators, with hands-on experience in C++ concurrency, chipset stress testing, and power/performance tuning. Has deployed on-device AI models and built deployment/log post-processing workflows using Docker/Kubernetes and CI/CD; interested in translating this embedded AI/performance background into robotics (perception/real-time systems).

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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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RK

Rahul Konala

Screened

Senior Strategy Consultant specializing in AI, SaaS, and TMT

New York, New York6y exp
Strategy&Texas A&M University

Cross-functional operator/program leader with experience running end-to-end platform and governance assessments and translating findings into OKRs and annual roadmaps. Central contributor to a large post-merger integration overseeing 15+ functions and identifying ~$55M in cost reallocation opportunities through headcount, process, and technology optimization.

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NJ

Mid-level Applied AI Engineer specializing in LLM agents, RAG, and model alignment

Chicago, IL3y exp
Medhastra AINorthwestern University

Applied Scientist with legal-tech experience who builds production LLM systems. Created and deployed Quibo AI, a LangGraph-based multi-agent pipeline that turns large markdown/Jupyter inputs into polished blogs and social posts, overcoming context limits via ChromaDB + HyDE RAG. Also built a large-scale iterative code-evolution workflow using multi-model orchestration (GPT/Claude/Gemini) with testing, debugging loops, and evaluation/observability practices.

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SA

Suhas Athreya

Screened

Junior Salesforce & AI Product Consultant specializing in public sector and enterprise platforms

Bengaluru, India2y exp
Overleap NetworksCarnegie Mellon University

Software/cloud engineer with PwC experience deploying a nationwide Australian Government Salesforce labor licensing platform used by 200k+ professionals, emphasizing safe integration, CI/CD, and UAT-driven quality improvements (40% defect reduction). Also built a Python/FastAPI RAG system with the U.S. Army to convert CONOP documents into risk assessments, adding human-in-the-loop and provenance features to address operator trust concerns.

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VC

Mid-level Growth & Digital Marketing Manager specializing in e-commerce and enterprise demand gen

San Francisco, CA6y exp
AmazonUniversity of Texas at Arlington

Growth creative lead at Amazon who ran structured, incrementality-informed A/B tests for Prime acquisition on Amazon DSP. Produced a winning benefit-led video + social-proof framework that improved CTR/CVR while cutting CPA (-24%) and increasing ROAS (+32%), then scaled the approach across email and onsite placements for an additional 10–12% lift in Prime sign-ups.

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PP

Senior AI Engineer specializing in LLMs, RAG, and multimodal NLP

Austin, TX5y exp
Health Care Service CorporationUniversity of Florida

Built a production LLM/RAG assistant for insurance/health claims agents that ingests 100–200 page patient PDFs via OCR (migrated from local Tesseract to Azure Document Intelligence) and delivers grounded claim detail retrieval plus summaries with PII/PHI guardrails. Experienced orchestrating large workflows with Celery worker pipelines and AWS Step Functions (S3-triggered, Fargate-based batch inference/accuracy aggregation), and collaborates closely with non-technical SMEs (claims agents/nurses) through shadowing, iterative demos, and SME-defined evaluation.

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MK

Maya Kundakci

Screened

Junior Robotics & Controls Engineer specializing in autonomous navigation and UAV systems

Pittsburgh, PA1y exp
Carnegie Mellon UniversityCarnegie Mellon University

Robotics software engineer with extensive ROS2 experience building and integrating full autonomous navigation stacks (sensor fusion, ICP/occupancy-grid mapping, planning). Hands-on computer vision work for drones, including monocular depth-from-RGB pipelines (Open3D/OpenCV) and model swaps to improve low-light performance. Also experienced in multi-drone coordination with Crazyswarm2 and Vicon-based state estimation, plus Gazebo simulation for TurtleBot, Franka Emika, and a Lunabotics-style excavation rover.

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MN

Meghashree N

Screened

Mid-level AI/ML Engineer specializing in recommender systems, NLP, and cloud ML

Remote, USA7y exp
Lincoln FinancialUniversity of Arizona

AI/ML engineer who has shipped both a safety-critical mental health RAG chatbot (Mistral 7B + Pinecone) with automated faithfulness/toxicity monitoring and a deep Q-learning investment recommendation engine at Lincoln Financial Group. Strong in production MLOps and orchestration (AWS Lambda/CloudWatch/SageMaker, Docker, AKS) and in translating regulated-domain requirements (clinical reliability, fiduciary duty) into measurable model constraints and monitoring.

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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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AS

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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FA

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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AR

Amy Russ

Screened

Director-level Applied Science & AI/ML leader specializing in LLMs, RAG, and MLOps

Atlanta, GA9y exp
HertzUniversity of Tennessee, Knoxville

Active in the venture ecosystem as a Rogue Women's Fund fellow and angel investor, with memberships in Gaingels and Angel Squad (HustleFund). Interested in founding a company to leverage extensive experience, and evaluates ideas through market need and economic viability of the target population.

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PK

priya kotha

Screened

Mid-level Data Engineer specializing in real-time pipelines across FinTech and Healthcare

USA, USA4y exp
PlaidSacred Heart University

Data engineer at Plaid who built greenfield, end-to-end real-time transaction pipelines and FastAPI data services for fraud detection and analytics, handling millions of events per day. Strong focus on reliability and data integrity via Great Expectations validation, Airflow-based monitoring/SLAs, quarantine/staging patterns, and robust external data ingestion with schema versioning and backfills (reported 50% fewer anomalies and ~40% fewer failures).

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CL

Changhee Lee

Screened

Mid-level Software Engineer and Product Manager specializing in AI and financial data platforms

Remote4y exp
AI MelodyCornell University

Full-stack engineer with deep Next.js App Router + TypeScript experience who has shipped and owned production features in a fashion/wardrobe/resale domain. Demonstrated measurable impact across the stack: +25% engagement, 30% faster load times, 40% fewer errors, plus durable Temporal workflows and Postgres analytics/query tuning for real-time dashboards.

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TJ

Senior Full-Stack Software Engineer specializing in FinTech payments and fraud systems

Plano, TX8y exp
AffirmTexas Tech University

Backend/data engineer with production experience building credit/fraud enrichment services and checkout pipelines on AWS (EKS + Lambda) using FastAPI, Kafka, Postgres, and Redis, with a strong focus on reliability patterns (timeouts/retries/circuit breakers) and observability. Has also built AWS Glue/PySpark ETL into S3/Redshift with schema evolution and data quality controls, and modernized legacy credit decisioning into Java/Node microservices with parallel-run parity validation and feature-flag rollouts.

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VM

Junior AI/ML Engineer specializing in LLM agents, explainable AI, and computer vision

Durham, North Carolina1y exp
Duke UniversityDuke University

Robotics/computer-vision engineer with industrial safety monitoring experience, building real-time pose estimation (TRTPose) and 2D-to-3D localization and optimizing pipelines to sustain 30+ FPS under heavy multi-entity load. Also brings edge-to-cloud distributed systems work (HoloLens + Google Vision/Translation) and production ML deployment experience using Docker/CI/CD across finance and edge camera environments.

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NS

Nick Stoianov

Screened

Executive CTO & AI Systems Architect specializing in cloud platforms and RAG products

Los Angeles, CA23y exp
CTOlogySaybrook University

Technology leader with experience owning enterprise roadmaps and executing large-scale platform standardization during rapid M&A—most notably driving a tech roadmap across a 37-company portfolio at Regent, tackling technical debt and security gaps via unified cloud-native architecture, IAM/logging, CI/CD, and a global SRE model. Previously scaled an Adobe engineering org from 8 to 40+ across four regions, implementing clear org design, KPIs, and an extreme-ownership culture to support 24/7 operations and enterprise needs.

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MC

Matthew Cason

Screened

Senior Strategy & Venture Investing Professional specializing in deep tech and energy

Los Angeles, CA7y exp
Fulcrum Venture GroupUniversity of Chicago

Operator/Chief-of-Staff-style leader with experience spanning a seed-stage aerospace startup, Capital One, and Oasis Financial. Has led multiple executive-driven cross-functional initiatives, built hiring and data/dashboard systems (Tableau) to increase executive leverage, and managed strategic product transformation work alongside day-to-day operational execution.

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CM

Intern/Junior Software Engineer specializing in ML, networking telemetry, and full-stack web apps

Louisville, CO1y exp
CableLabsUniversity of Colorado Boulder

Backend-focused engineer with hands-on experience modernizing a legacy SNMP/PNM data collection system at CableLabs into a cloud-accessible Kubernetes pipeline, feeding Prometheus-formatted metrics into VictoriaMetrics and visualizing real-time network health in Grafana for 100+ modems. Also built a FastAPI + Supabase appointment booking portal for a clinic with encryption and phone-number-based auth, and has frontend experience debugging S3-based HEIF image rendering issues.

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