Gen AI Practitioner-Coach - Enterprise AI Advisory & Knowledge Broker

The task will be to work as an adviser to enterprise engineering teams on generative AI systems and architectures through hands-on coaching, mentoring, and knowledge-brokering. Serve as a trusted technical advisor and community facilitator, driving organizational adoption of agentic AI architectures, AI-assisted development workflows, and advanced prompt engineering patterns. Work Embedded within the engineering organization to elevate collective capability and foster sustainable knowledge-sharing practices across teams.

Technical Proficiency:

• Enterprise LLM APIs and orchestration frameworks
• AI-assisted coding tools and agentic development paradigms
• Cloud platforms (Azure preferred)
• Python and TypeScript/JavaScript
• Source control systems and collaborative development practices
• Community-of-practice facilitation and knowledge-transfer methodologies

Desired Candidate Attributes:

• Coaching mindset: Advise and guide teams without imposing design decisions; ask powerful questions and enable discovery
• Collaborative spirit: Embed naturally within large engineering organizations; mentor and support distributed teams
• Proven expertise: 10+ years overall engineering experience; 3+ years specialized in generative AI systems
• Hands-on capability: Can write, review, and reason about code; comfortable pairing with engineers
• Learner's mindset: Stay current with rapidly evolving GenAI landscape; experiment and iterate
• Communication skills: Articulate complex technical concepts to diverse audiences; facilitate workshops and knowledge sessions
• Systems thinking: Understand how agentic systems interact with existing enterprise infrastructure and workflows
• Initiative: Self-directed; comfortable identifying improvement opportunities and proposing solutions

Additional Information:

• Enterprise LLM endpoints (company API subscription)
• Licensed AI coding tools (GitHub Copilot, Cursor, or Claude Code)
• GitHub, Jira, Microsoft Teams, SAP Fieldglass
• Standard developer environment and VPN access

Key Deliverables:

• Technical assessments and maturity evaluations
• Coaching sessions on agentic architectures and prompt engineering
• Code reviews and pair programming support
• Community of practice facilitation
• Best practice documentation and knowledge transfer