Schedule a call with a Leland team member who can help you explore your options.
Schedule a call
Work 1:1 with an expert to build practical skills in AI agents and automation, one of the most valuable capabilities for AI engineers today. Possible uses of coaching sessions, but not limited to: - Single and multi-agent system architecture - Agent prompt and instruction design - Tool use and API integration for agents - Building automation workflows with AI decision steps - Agent evaluation, reliability testing, and failure handling - Production deployment and monitoring of agentic systems - AI code review on your agent projects
Hands-on experience designing and building AI agents for real use cases
Skills to architect multi-agent systems with proper handoffs and error handling
The ability to evaluate and improve agent performance over time
A foundation for building increasingly sophisticated AI automation
Coaching delivered via live sessions and .
Services included:
Technical Skills
Prompt Engineering
AI Research
Model Development
AI System Design
ML Ops & Deployment
AI Code Review
Schedule a call with a Leland team member who can help you explore your options.
Schedule a call
Get help with AI Fundamentals, Prompt Engineering, and .

Joined June 2026
Build production-ready AI and ML systems
I bring hands-on experience in AI, machine learning, data science, and production-grade GenAI engineering, with a focus on building practical solutions that solve real business problems. My experience includes designing and implementing AI-powered applications, RAG systems, LLM-based analytics tools, and agentic solutions that help teams automate workflows, retrieve knowledge, and generate insights from enterprise data. I have built agentic AI solutions using different frameworks and implemented them in production environments. I have worked across the full lifecycle, from problem definition and prototype development to model integration, evaluation, deployment, and scaling. My experience also includes implementing key production components such as memory, observability, traceability, human-in-the-loop workflows, evaluation, and guardrails. I can help customers understand not only the concepts behind AI and ML engineering, but also the practical architecture and implementation steps needed to move from prototype to reliable production-ready AI systems.
5h+ of coaching