Lead Engagement Director
Skills
About This Role
Key Responsibilities
- Lead Complex AI Engagements: Own the end-to-end delivery lifecycle for high-stakes professional services engagements. You will manage the 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). You will ensure business goals are accurately translated into technical requirements.
- Technical Risk Management: Leverage your technical background to identify implementation risks early whether related to data infrastructure, API integrations, or agent logic and work with the engineering team to mitigate them before they impact the critical path.
- Stakeholder Management: cultivate strong, trusted relationships with client sponsors. You will manage expectations, handle escalations, and navigate complex organizational dynamics to ensure project success.
- Drive Adoption & Change: Go beyond delivery by helping 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 the delivery team maintains 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 ( Consulting DNA )
- Disciplined approach to project governance, documentation, and client communication
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