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Vetted Generative AI Professionals
Pre-screened and vetted.
Mid-level Generative AI Engineer specializing in LLMs, RAG, and agentic AI
Mid-level Product Manager specializing in AI-driven product strategy and analytics
Executive Technology Leader specializing in AI, Cloud, and FinTech/EdTech platforms
Senior Data Scientist specializing in ML, fraud risk, and Generative AI (RAG/LLMs)
Mid-level AI/ML Engineer specializing in GenAI, computer vision, and real-time ML pipelines
Senior Software Engineer specializing in distributed AI/ML and GenAI platforms
Senior Full-Stack AI/ML Engineer specializing in personalization, NLP, and GenAI platforms
Senior ETL/Data Engineer specializing in cloud data platforms and AI/ML-ready pipelines
Mid-level Data Scientist / ML Engineer specializing in LLMs and predictive analytics
Staff UX/Product Designer specializing in enterprise cloud and AI-driven experiences
Senior Customer Success Manager specializing in Enterprise SaaS retention and AI enablement
Senior Full-Stack Engineer specializing in cloud-native Java microservices and GenAI
Senior Data Scientist specializing in healthcare analytics and scalable ML pipelines
THAMES HARRISON
Engineering Manager specializing in enterprise SaaS, cloud architecture, and AI/ML
“Senior engineering manager who stays hands-on (~50/50) while leading teams through design reviews, code reviews, and production issue triage. Shipped scalable platform features (notifications, user action tracking via microservices) with strong quality/performance practices (TDD, high-load testing). Owned a complex cross-system SSO/IdP incident end-to-end, identifying a SameSite+iFrame root cause and delivering a configurable product fix plus support documentation.”
Rafael Ortega
Senior Full-Stack & AI Engineer specializing in LLM integrations and cloud-native systems
“Backend/data engineer with hands-on production experience building FastAPI Python APIs and AWS-native platforms (Lambda/API Gateway, SQS, ECS Fargate) with Terraform + GitHub Actions CI/CD and strong reliability practices (JWT/RBAC, retries/timeouts, structured errors/logging). Also built AWS Glue ETL pipelines (S3/RDS to curated S3/Athena) with schema evolution and data quality controls, modernized legacy processing via parallel-run validation and phased cutovers, and has demonstrated SQL tuning impact (seconds to <200ms) plus incident ownership for batch pipeline SLAs.”
Pavan Kalyan
Mid-level AI Engineer specializing in GenAI agents and RAG for IT operations
“Built and operates a production LLM agent for enterprise IT operations that triages and drafts resolutions for high-volume ServiceNow tickets using LangChain + RAG (Pinecone/pgvector) and AWS Bedrock/OpenAI. Emphasizes reliability with schema-validated stages, offline eval datasets from real tickets, and CloudWatch-driven monitoring/guardrails; system scales to 40K+ tickets/month and cut resolution time ~28%.”
Mid-level AI/ML Engineer specializing in conversational AI, NLP, and LLM-powered RAG systems
Senior Machine Learning Engineer specializing in MLOps and Generative AI
Senior Data Engineer specializing in multi-cloud data platforms and generative AI