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Vetted Databricks Professionals
Pre-screened and vetted.
Mid-level AI/ML Engineer specializing in LLMs, RAG pipelines, and multi-agent systems
Senior Data Scientist specializing in NLP, LLMs, and Generative AI automation
Junior AI Engineer specializing in LLM systems and network automation
Staff Full-Stack Engineer specializing in cloud microservices and AI-enabled platforms
Senior Agentic AI & Backend Engineer specializing in LLM platforms and multi-agent systems
Senior Data Scientist specializing in Generative AI and LLM evaluation
Staff-level Data Scientist specializing in LLMs, NLP, and product experimentation
Senior Machine Learning & GenAI Engineer specializing in LLM systems and data pipelines
Senior AI/ML Engineer & Data Scientist specializing in NLP, entity resolution, and knowledge graphs
Mid-level Machine Learning Engineer specializing in LLMs, ranking, and scalable ML systems
Executive Technology Leader specializing in Cloud, Data Platforms, and AI/ML
Senior Software Engineer specializing in cloud platforms for healthcare and e-commerce
Senior Data Scientist specializing in large-scale ML systems and recommendations
Executive Software Engineering Leader specializing in AI/ML, cloud platforms, and distributed systems
Christopher Chu
Senior Backend Engineer specializing in distributed systems and cloud microservices
“Backend/data engineer with experience at Nike building high-volume order orchestration and validation APIs using FastAPI microservices on AWS EKS with Kafka, Redis, and Postgres. Strong in production reliability (timeouts/retries/idempotency), GitOps (Argo CD) + Terraform deployments, and data pipelines (AWS Glue/S3), with hands-on incident ownership and legacy modernization into API-driven services.”
Akhil Maram
Senior Data Engineer specializing in real-time data platforms and lakehouse architectures
“Senior, product-focused engineer who has built real-time customer-facing web applications and a microservices backend (TypeScript/React/Node) using RabbitMQ, MongoDB, and Redis. Demonstrates strong operational maturity (idempotency, tracing/observability, backpressure) and built an internal console that became the primary tool for debugging, replaying jobs, and managing system behavior.”
Jeffery Faneuff
Executive Engineering Leader specializing in AI-driven SaaS and IoT platforms
“Engineering leader who built and delivered an IoT smart-spaces platform for the self-storage and smart-living domains, translating customer requirements into architecture, capability maps, and a multi-milestone roadmap. Personally stood up missing AI/ML capabilities (including churn prediction) using Databricks (Delta Lake/MLflow), enabling follow-on features like energy optimization and security/anomaly detection. Scaled an org from 20 to 80+ with disciplined Agile planning (Jira Advanced Roadmaps/Confluence) and strong executive/customer-facing leadership during high-stakes customer commitments.”
Dennis Noto
Executive Technology & Security Leader specializing in FinTech, AI platforms, and enterprise modernization
“Technology transformation leader who builds board-approved roadmaps and scales engineering orgs with strong Agile execution. Led large modernization efforts (e.g., Scottrade: 3,000 programs/4M LOC in 18 months) and scaled POCs into enterprise SaaS platforms using Docker, Kubernetes, Helm, and Terraform for high-concurrency workloads.”
Harish Kasu
Mid-level AI/ML Engineer specializing in Generative AI, RAG, and MLOps
“AI/LLM engineer with production experience at NVIDIA and Microsoft, including building a RAG-based enterprise knowledge assistant that improved accuracy by 42% and scaled to thousands of queries. Deep in inference optimization (TensorRT-LLM, Triton, quantization, speculative decoding) and MLOps/observability (Prometheus/Grafana, MLflow, LangSmith), plus orchestration with Kubeflow/Airflow across multi-cloud.”