Vetted SQL Professionals

“Operations/product leader with experience integrating product organizations after acquisitions, standardizing Agile/PDLC and RACI to remove ambiguity and enable on-time launches. Hands-on in implementing Jira-based execution frameworks and mentoring exec teams on KPI/OKR operating cadence, including adopting a Product/Engineering/UX triad model to reduce rework and improve customer alignment.”

“Software engineer who built and deployed OddPulse, a multi-agent LLM-powered continuous financial auditing system aimed at reducing compliance penalties by catching issues before audit cycles. Experienced with TrueAI-based agent orchestration, Airflow on GCP batch workflows, and rigorous evaluation/benchmarking (hit rate/MRR, latency/TTFT, cost) alongside security controls for sensitive financial data.”

“Completed an Amazon externship building a GPT-4 + RAG pipeline to summarize themes from hundreds of employee reviews for workforce analytics aimed at improving warehouse retention. Emphasizes production-readiness through labeled-data evaluation, source attribution for explainability, human-in-the-loop review, and rigorous data cleaning/observability to debug real-world LLM workflow issues.”

“Full-stack engineer with strong DevOps/AWS production experience who builds and operates multi-agent AI systems end-to-end (Streamlit/Python through Docker/Kubernetes and ECS/Fargate). Has delivered measurable outcomes: sub-2s latency and ~92% routing accuracy for an AI wellness assistant, shipped an AI-for-BI prototype in under 6 weeks cutting analysis time ~40%, and improved pipeline iteration speed ~35% via modularization and CI/regression checks.”

“Technology executive (VP/SVP Engineering, CTO/co-founder) with ~17 years of roadmap execution and the last 7 in senior exec roles. Notably led an AI-first strategic pivot when generative AI emerged—creating the AI product strategy, reskilling teams, and shipping initial AI features—while also scaling engineering orgs using SPACE metrics and driving major architecture decisions (custom reporting with React + Redshift) to close competitive gaps.”

“Engineering manager leading a 15-person team at FBN on the Gridbull platform, shipping a self-serve pricing/quoting tool for structured commodity products using real-time futures market data. Owns architecture and reliability for third-party data integrations (WebSocket + REST fallback), including resolving a day-one production incident caused by undocumented vendor connection resets. Introduced lightweight Technical Implementation Plans to improve cross-functional alignment and delivery speed in a high-growth environment.”

“Customer Success Manager with enterprise experience managing the Walgreens contract at EarnIn end-to-end, coordinating executives/legal/HR/marketing and technical teams through benefits-platform integration, adoption, and renewal. Delivered 85% annual retention (despite store closures) and maintained a positive NPS, supported by usage monitoring, benchmarking, and monthly executive reporting. Also drove expansion at Unison by rolling out new insurance products to homeowners using savings/ROI-based positioning.”

“CTO who ties technology strategy directly to business outcomes, building multi-year roadmaps with measurable ROI. Led major modernization (cloud, data platform, unified API, microservices + CI/CD) delivering 5x faster releases/deployments, 99.8% uptime, and 40% user growth without headcount increases, while scaling engineering from 15 to 80+ in ~18 months.”

“Full-stack engineer with startup experience who owned end-to-end features on Impact’s Hiring Solutions platform, including a hiring inbox spanning React UI and Postgres data models; the product helped drive 500+ jobs filled shortly after launch. Comfortable designing modern React/TypeScript + Node architectures (GraphQL, testing, migrations) and operating on AWS (RDS, EC2/Fargate, S3, Datadog, CircleCI). Also founded their own startup (Bibbr) and made early-stage stack/infrastructure decisions under high ambiguity.”

“Software engineer with hands-on experience building a distributed ticketing system on AWS (Terraform, Go, MySQL) focused on high-concurrency reliability (locks/queues to prevent duplicate ticket confirmations) and load-tested performance. Also independently owned and shipped an Airflow automation script to stop/restart workflows during deployments with email notifications, reducing manual operational effort.”

“Full-stack engineer with fintech/trading domain experience (Fidelity) and startup SaaS CRM/billing platform work (Zoho), building real-time portfolio analytics and trade-processing systems. Strong in microservices, event-driven architectures (Kafka/WebSockets), and AWS/Kubernetes operations with measurable performance gains (~34–35% latency reduction) and maintainability improvements (~40% faster deployments). Targeting a founding full-stack engineer role in NYC with meaningful equity.”

“Built and operated a production TypeScript backend for a stateful conversational quoting chatbot at Tringapps, orchestrating multi-step workflows and session state while integrating with Salesforce and NetSuite. Implemented validation/retry logic, modular architecture, and strong logging/observability to handle real-world edge cases and external API failures.”

“Forward-deployed engineer/tech lead who built an end-to-end demand planning and forecasting application for a major US steel manufacturer, integrating Snowflake data into the C3 platform with batch/MapReduce workflows, monitoring, and a React/TypeScript UI. Also productionized an enterprise LLM integration with structured outputs and authorization guardrails, reporting +30% stakeholder engagement and broad adoption across customer deployments.”

“Software engineer with strong end-to-end ownership across frontend, backend, data, and infrastructure, including real-time systems (Kafka/Postgres) and observability (Datadog). Built and productionized an AI-native RAG support assistant (OpenAI embeddings + Pinecone) with prompt/guardrail design, achieving 48% agent adoption and 30% faster responses. Experienced in legacy modernization and reliability work using feature flags, event/transaction replay, and rapid embedded delivery.”

“Built and productionized an internal LLM-powered document Q&A system at Morgan Stanley using a LangChain-based RAG pipeline (FAISS + OpenAI) with AWS ingestion (S3/Lambda), handling 100k+ pages and cutting lookup time ~35% while keeping responses under 3 seconds. Strong on reliability: automated evals/CI (pytest + GitHub Actions), CloudWatch monitoring, drift detection (prompt drift and fraud-model drift), and security controls (IAM + app-level authorization) in a financial-services environment.”

“Backend/full-stack engineer who has owned production systems end-to-end, including a Dockerized Node.js/TypeScript probabilistic fault-tree analysis service for nuclear safety research deployed on AWS. Also built and operated a FastAPI-based RAG pipeline over 200+ PDFs using FAISS, focusing on low-latency, idempotent workflows and strong observability; experienced with API design and Playwright E2E automation across React/Angular projects.”

“Built and shipped production LLM/RAG systems at Mayo Clinic, including a conversational AI assistant for patient pre-consultation and a clinical-trial matching tool for doctors. Implemented HIPAA-compliant de-identification and guardrails, plus real-time feedback logging and fine-tuning that improved response accuracy by 15% and reduced admin workload by 25%.”

“GenAI/LLMOps practitioner who deployed a production RAG-based customer service and knowledge retrieval system for a global bank using LangChain, FAISS/Azure Cognitive Search, GPT-4/Claude, and Guardrails—driving a reported 35% Q&A accuracy lift while reducing handle time and escalations. Also partnered with non-technical leaders at CVS Health to deliver ML-driven supply chain risk and inventory insights via anomaly detection, NLG summaries, and stakeholder-friendly dashboards.”

“Operations and customer-facing leader with deep last-mile logistics expertise from running a critical extra-large Amazon logistics hub end-to-end (inventory accuracy, throughput, yard efficiency), including scalable process improvements adopted across Amazon XL sites. Strong cross-functional and partner management (DSPs/carriers, engineering ops) with rapid incident resolution and VOC-to-product translation (geofence/map fixes). Also demonstrates land-and-expand growth motion from Cisco, expanding a standardized software platform across multiple global sites.”

“Backend engineer who built and scaled a blockchain-based e-voting platform at early-stage startup Elemential Labs, balancing decentralization with real-world operability by centralizing control-plane components while keeping the ledger immutable. Has hands-on experience migrating high-throughput ingestion from Kafka to AWS Kinesis with parallel cutover, strengthening data integrity and read-after-write consistency (Elasticsearch), and hardening pipelines against silent data-quality failures via anomaly detection and self-healing automation.”

“Game designer with shipped multiplayer FPS experience on XDefiant, owning end-to-end mode design and tuning (Capture the Flag) and co-designing the Hardpoint spawn system across maps. Builds and iterates prototypes directly in Unreal Engine 5 using Blueprints, and has navigated real console/engine performance constraints and post-launch fixes while maintaining competitive integrity.”

“Builder/technical leader who was brought into Finicity to turn a credit-improvement concept into a viable product—architected, staffed, and launched what became Experian Boost. Delivered a major North American product launch in ~6 months, scaling to ~50,000 new users per day at launch and solving complex ML classification and distributed processing/order-of-operations challenges on AWS.”

“Built and productionized a secure internal RAG-based AI assistant (LangChain/FastAPI/FAISS on GCP), tackling real-world issues like latency, retrieval speed, and hallucinations—delivering 25% faster retrieval and 99.9% uptime. Also implemented scalable, reliable ML retraining orchestration with AWS Step Functions/SageMaker/Lambda and partners closely with compliance analysts to iteratively refine prompts and outputs to meet governance standards.”

“Full-stack engineer focused on high-throughput document/financial data platforms, building Angular/React front ends and Spring Boot microservices with Python/Flask services for heavy processing. Experienced in designing non-blocking, asynchronous workflows (Celery/RabbitMQ) and deploying containerized systems to AWS ECS with auto-scaling and CloudWatch monitoring.”