AI Enablement Lead
- Act as a domain authority in AI across G&A, mentoring team members, setting technical standards, and guiding leadership on AI investments and roadmap prioritization.
- Develop and prototype solutions by building proof-of-concepts that leverage large language models (LLMs), agent frameworks, and workflow orchestration tools.
- Provide technical oversight by reviewing code and prompts, guiding system design decisions, and defining evaluation methodologies and performance benchmarks.
- Partner with business units to identify manual bottlenecks in Finance, HR, Sales, Supply Chain and Marketing applying AI to automate complex processes.
- Oversee integration and deployment by ensuring seamless connectivity between AI agents and enterprise systems through APIs, data pipelines, and workflow platforms.
- BS degree in Computer Science, or a related technical field, or equivalent practical experience
- 8-10 years of professional experience across data science, data engineering and business intelligence disciplines. 3+ years of technical experience with a focus on building and shipping AI/ML products
- Mandatory hands-on experience using GenAI tools (vibe-coding) to turn prompts into small prototypes in a constrained environment, then use that artifact to validate requirements.
- Strong proficiency in Python and experience with modern AI/ML frameworks (e.g. LangChain, Vertex AI Agent Builder, TensorFlow, PyTorch) and cloud platforms
- Experience with GCP, Vertex AI, A2A, MCP and ADK frameworks and their application in enterprise systems
- Excellent communication skills with the ability to articulate technical AI concepts to non-technical stakeholders
- Deep expertise integrating AI and LLM solutions securely with major enterprise SaaS platforms (e.g., Salesforce, SAP, Workday, ServiceNow) in a complex, global corporate environment
- Experience designing advanced agentic patterns (e.g., multi-agent orchestration, complex RAG architectures, dynamic tool use) for automating multi-step, cross-platform business workflows.
- Proven track record of influencing cross-functional leadership, driving technical strategy, and managing organizational change to ensure high user adoption of new AI tools across non-technical business units
- Strong understanding of AI governance, enterprise data privacy standards, and security protocols (e.g., RBAC, data loss prevention) when deploying AI applications on internal corporate data
- Demonstrated ability to navigate ambiguity and drive projects from conception to launch in a fast-paced environment
- Experience acting as a technical multiplier—mentoring team members, setting engineering standards for AI tooling, and guiding leadership on AI investments and roadmap prioritization.
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