Vetted NoSQL Professionals

“Data/ML engineer in financial services (Northern Trust) who built a production RAG-based LLM system to connect structured transaction/portfolio data with unstructured market and internal documents for risk teams. Strong in end-to-end pipelines (AWS Glue/Airflow/PySpark), entity resolution, and taking models from prototype to reliable daily production with performance tuning (LoRA + TensorRT) and monitoring.”

“Built and productionized an internal GenAI chatbot that makes company policy/SOP knowledge instantly searchable, using a secure RAG architecture on AWS (Bedrock/Titan embeddings/OpenSearch Serverless, Textract/Lambda/S3 ingestion, Claude 3 Sonnet). Demonstrates strong MLOps/orchestration experience (Airflow, Step Functions with Lambda/Glue/SageMaker) and a rigorous reliability approach (RAGAS metrics, A/B testing, citation validation, monitoring), including collaboration with compliance stakeholders via review dashboards.”

Sophie Adams

Screened ReferencesStrong rec.

Senior Full-Stack Engineer specializing in event technology and interactive systems

New York, NY20y exp

“Full-stack product engineer in event tech who has owned AI-powered web products from architecture to live production, including a no-code SaaS/marketplace for event activations and real-time AI kiosk experiences. Particularly strong in building for non-technical users in high-stakes live environments, with hands-on experience across Vue/Laravel, LLM workflows, image generation pipelines, and operational reliability.”

“ML/AI engineer with hands-on ownership of production recommendation and GenAI systems, spanning experimentation, deployment, monitoring, and iteration. Stands out for delivering measurable outcomes—22% CTR lift, 15% conversion lift, and a 30% reduction in support tickets—while demonstrating strong judgment on latency, cost, and safety tradeoffs in real-world systems.”

Kris Wen

Screened ReferencesModerate rec.

Mid-level Software Engineer specializing in AdTech and AI-enabled web engineering

San Francisco Bay Area, CA4y exp

“Software engineer at American Express who built a zero-to-one first-party cookie tracking architecture as the industry moved away from third-party cookies, combining frontend, backend, CI/CD, and AI-assisted QA automation. Particularly strong in developer tooling and workflow automation, with measurable impact including 70% less manual QA, 8+ critical errors caught pre-production, and PR cycles reduced from 48 hours to under 8.”

“Software engineer with hands-on experience shipping production AI agents and end-to-end ecommerce workflows. They built a customer support automation agent with strong guardrails and evaluation practices, then improved it post-launch using real user data to cut latency ~30% and token cost ~25%. Also drove a zero-to-one self-serve order modification product across React UI, backend services, and cross-functional alignment.”

“Backend Python engineer focused on production-grade automation and reliability, with hands-on experience designing scalable API systems on PostgreSQL and making pragmatic architecture calls (modular monolith over premature microservices). Demonstrated measurable performance wins (50–60% latency reduction) and strong operational rigor via observability, incremental rollouts/feature flags, and security patterns like JWT + RBAC + database row-level security.”

Viacheslav Bulba

Screened

Senior QA Automation Engineer specializing in UI/API test automation and CI/CD

Las Vegas, Nevada15y exp

“QA professional with 15+ years testing a variety of applications (not games), experienced partnering with developers/designers/product owners across the feature lifecycle. Brings a disciplined, methodology-driven approach to test design, regression coverage, and high-quality defect reporting using tools like Jira, TestRail, qTest, and HPQC; targeting ~100K base (flexible based on total package).”

Job DelToro

Screened

Senior Full-Stack Engineer specializing in SaaS, cloud infrastructure, and video platforms

Guadalajara, México8y exp

“Full-stack engineer working at the intersection of product engineering and applied AI, with hands-on experience shipping real-time user features, MCP server integrations, and LLM-powered support systems. Stands out for combining TypeScript-heavy full-stack execution with production AI practices like retrieval architecture, confidence-based routing, observability, and evals, while driving measurable outcomes such as a 25% DAU lift and reduced support load.”