Senior Engagement Director
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Key skills for this role
About the Role
Lead complex AI engagements, manage stakeholder relationships, ensure technical risk management, and drive adoption of AI solutions with strong business acumen.
Key Skills for This Role
Responsibilities
- Lead complex AI engagements: own end to end delivery lifecycle for high stakes professional services engagements
- Bridge business and technology: act as primary translation layer between client business stakeholders and technical delivery team
- Technical risk management: identify implementation risks early and work with engineering team to mitigate them
- Stakeholder management: cultivate strong, trusted relationships with client sponsors
- Drive adoption and change: help customers operationalize and adopt Agentic workflows
- Agile delivery: run agile sprints, stand ups, and sprint reviews
Requirements
- Technical fluency: understanding of system architectures, API integrations, and cloud infrastructure
- Ability to engage in discussions on the software development lifecycle (SDLC) with engineering teams
- Familiarity with GenAI and Agentic systems (e.g., non deterministic behavior, latency trade offs, MCP servers, RAG architectures)
- Business acumen: ability to define KPIs, measure ROI, and align technical outputs with strategic business objectives
- Consulting mindset: disciplined approach to project governance, documentation, and client communication
Full Job Posting
Key Responsibilities
- Lead Complex AI Engagements: Own the end to end delivery lifecycle for high stakes professional services engagements. Manage scope, timeline, budget, and execution of projects building GenAI agents and predictive solutions.
- Bridge Business & Technology: Act as the primary translation layer between client business stakeholders (up to the C suite) and DataRobot's technical delivery team (AI Engineers and Data Scientists). Ensure business goals are accurately translated into technical requirements.
- Technical Risk Management: Leverage technical background to identify implementation risks early and work with engineering team to mitigate them before they impact the critical path.
- Stakeholder Management: Cultivate strong, trusted relationships with client sponsors. Manage expectations, handle escalations, and navigate complex organizational dynamics.
- Drive Adoption & Change: Help customers understand how to operationalize and adopt Agentic workflows, advising on process changes required to integrate AI agents into their daily operations.
- Agile Delivery: Run agile sprints, stand ups, and sprint reviews, ensuring high velocity and clear direction.
Technical Fluency
- Understanding of system architectures, API integrations, and cloud infrastructure
- Ability to engage in discussions on the software development lifecycle (SDLC) with engineering teams
- Familiarity with GenAI and Agentic systems (e.g., non deterministic behavior, latency trade offs, MCP servers, RAG architectures)
Business Acumen
- Ability to define KPIs, measure ROI, and align technical outputs with strategic business objectives
Consulting Mindset
- Disciplined approach to project governance, documentation, and client communication
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