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Tech Stack
Tools & technologiesCloud
About the role
Key responsibilities & impact- Lead Unanet’s internal data strategy and architecture for its AI transformation
- Define a shared data foundation and practical roadmap for AI
- Assess the current data environment and prioritize gaps, owners, dependencies, and outcomes
- Use priority AI initiatives to test architecture and develop reusable approaches
- Define how internal data is organized, connected, secured, and made available to AI tools, agents, and workflows
- Set standards for data access, permissions, integration, compatibility, and reuse
- Create repeatable methods for providing reliable context to AI solutions and enabling safe source-system interaction
- Evaluate data platforms and integration options based on business needs, security, cost, and maintainability
- Work with technical teams and system owners to implement, test, and validate architecture decisions
- Establish data quality, metadata, source-of-truth, ownership, and stewardship requirements
- Apply governance, privacy, and risk processes to AI data with Legal, Security, IT, and business owners
- Assess AI data readiness and identify requirements for scaling solutions
- Coordinate business owners, AI builders, technical specialists, security partners, and system experts
- Support business-led experimentation and connect successful work to shared architecture
- Advise senior leaders and key partners on AI data priorities, tradeoffs, and investments
- Build agreement across functions and lead work involving systems owned by other teams
- In the first 90 days, assess Unanet’s internal data environment, define an initial target architecture and prioritized implementation plan, test it through priority initiatives, and establish decision paths with IT, Cloud Operations, Engineering, Security, Finance, GTM Systems, and functional data owners
Requirements
What you’ll need- Deep knowledge of designing data and knowledge foundations for enterprise AI using structured and unstructured data
- Strong understanding of how AI assistants, agents, and workflows use enterprise data, including retrieval, grounding, context, identity, metadata, and permissions
- Practical knowledge of cloud data platforms, integration, data modeling, data quality, governance, lineage, freshness, and monitoring
- Ability to design secure, reliable ways for AI systems to access and, when appropriate, update source systems
- Ability to move between strategy, architecture, and technical details while staying focused on business needs
- Sound judgment about what to standardize, simplify, and prioritize
- Ability to influence senior leaders and key partners across functions without direct authority
- Clear written and verbal communication skills, including explaining technical issues in plain language
- Practical, collaborative approach to problem-solving in a fast-moving environment
Benefits
Comp & perks- Employee equity
- Discretionary bonus compensation
- Participation in Unanet’s employee benefits plans and programs