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cBEYONData + SMX is seeking an AI Solution Lead - Hands-on Delivery to lead a small AI cell that enables and accelerates AI adoption across multiple project teams (e.g., business exploration/requirements, community transformation, delivery teams). You will listen to each team’s needs, translate them into a cohesive set of AI objectives and KPIs, and then build and promote reusable patterns (templates, automations, reference solutions) that teams can adopt. This is a player/coach role: you will still build—hands-on—while coordinating and influencing across the program.
Job Responsibility:
Cross-team AI enablement: Partner with other team leads to understand needs, identify opportunities, and remove blockers.
AI objectives & KPIs: Define and socialize practical AI objectives (e.g., cycle-time reduction, quality improvements, adoption) and establish KPIs/measurement approaches
refine them as teams learn.
Use-case intake & prioritization: Run an intake process (lightweight) to capture ideas, size effort, assess risk, and prioritize work for the AI cell (and recommend what other teams can implement independently).
Reusable solution patterns: Create repeatable AI building blocks: prompt/playbook standards, RAG patterns, governance checklists, evaluation approaches, and “how-to” guides.
Hands-on delivery: Build and ship select high-impact AI workflows/automations—especially those that require shared data access, deeper integration, or higher governance.
Palantir Foundry-centered implementation (preferred): Where applicable, implement AI workflows and data patterns in Palantir Foundry and help teams use those patterns effectively.
Community of practice: Facilitate a simple cadence (show-and-tell, office hours, examples library) so multiple teams can share learnings and scale adoption.
Guardrails & risk partnership: Coordinate with security/data owners to ensure safe use (data classification, access controls, auditability) and provide guidance to teams implementing AI.
Change enablement: Promote successful use cases, publish quick wins, and drive adoption through training, comms, and “starter kits.”
Requirements:
Demonstrated performance in a solution delivery roles (data/automation/software), including applying AI/LLMs in production or enterprise settings.