IBM AI and Machine Learning Engineer
Level 3 MLZ engineering for IBM z/OS: building Bob-powered coding agents, customer-driven AI workflows, and sub-100ms inference paths for enterprise systems.
Overview
This city represents the MLZ chapter: IBM's z/OS machine-learning work where AI has to survive enterprise constraints, customer pressure, and performance expectations that are far stricter than a toy demo.
Bob is IBM's coding-agent environment, closer in spirit to Codex or Cursor than to a chatbot. Phil builds and shares agents that automate Jenkins debugging, documentation creation, and team workflows so AI becomes a practical extension of daily engineering.
The technical edge is the environment: z/OS, Level 3 customer support, high availability, high RAS expectations, AI acceleration, and inference paths that need to perform in the sub-100ms range.
Buildings
- Builds Bob-based agents that automate Jenkins debugging, documentation creation, and repeatable team workflows.
- Works on MLZ Level 3 support, resolving customer issues while feeding real-world findings back into development direction.
- Ships AI/ML work for a demanding z/OS environment where inference latency, RAS, availability, and enterprise reliability all matter.
Production Queue
- Turn recurring engineering and customer-support workflows into reusable agent systems.
- Keep pushing enterprise AI toward fast, reliable, operationally useful inference rather than demo-only intelligence.
Tech Tree
- Bob
- Agentic AI
- Machine learning
- z/OS
- Jenkins
- AI acceleration
- Enterprise inference
Diplomacy
- z/OS engineering
- AI product teams
- Support teams
- Enterprise stakeholders
Trade Routes
- Coding agents
- Jenkins debugging
- Documentation automation
- Level 3 customer feedback
- Sub-100ms inference
Wonders
- Bob agent workflows
- MLZ Level 3 bridge
- Enterprise AI inference