AI Engineer

viva is building an internal AI Enablement program to accelerate practical, organization-wide adoption of AI. In this role, you will act as a central builder and operator for shared enablement capabilities, working closely with AI Enablement leadership, embedded AI coaches, and other teams.

You will help turn team use cases into reusable skills, agents, templates, workflows, and knowledge assets. The goal is to improve discoverability, reduce duplication, and make it faster for teams to onboard and apply AI in their day-to-day work.

What you will do

• Build and maintain the AI Skills, Agents, and Templates Hub.
• Develop reusable AI skills, agents, workflows, and starter templates.
• Create onboarding material, documentation, and best practices.
• Manage intake, prioritization, and tracking of AI enablement requests.
• Support AI coaches in packaging and scaling successful team solutions.
• Measure adoption, maintain asset quality, and coordinate releases.

How the team works

AI coaches identify use cases, provide domain expertise, validate solutions, and drive adoption within their teams. AI Enablement leadership sets priorities and strategic direction, complementing the embedded coach model announced across DSG.

Requirements

• Python expertise
• GitHub
• AWS is a plus
• AI frameworks (example: Langchain)
• MCPs
• RAG and Vector Database
• Harness Engineering

Technologies you may use

• Python
• GitHub
• AWS
• Langchain
• MCPs
• RAG
• Vector Database
• Harness Engineering
• Databricks

Success measures

• Increased adoption of AI tools and resources
• Growth of reusable skills, agents, and templates
• Faster onboarding and knowledge sharing
• Reduced duplication of effort across teams
• Improved discoverability and reuse of AI solutions

Nice to have

• Big Data (Databricks)
• Multi-agent system design and development

Location: Austin, TX (onsite). Compensation: USD 60–65 per hour.