Lead Engagement Director

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.

Knowledge, Skills and Abilities

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.

Requisite Education and Experience / Minimum Qualifications

• Related Experience: 7+ years of professional experience, including delivery of complex software or data products for enterprise clients
• Hybrid Background: Experience in technical roles (e.g., Software Engineer, Solution Architect, Technical Lead) with progression into client-facing leadership roles (e.g., Engagement Manager, Technical Program Manager, Product Owner)
• AI/ML Experience: Experience managing data science or machine learning projects
• Education: Technical undergraduate degree (Computer Science, Engineering, or similar); MBA preferred
• Certifications: PMP, Scrum Master (CSM), or cloud certifications (AWS, Azure, GCP) preferred
• Consulting Experience: Experience working within a management consulting or technology consulting environment (Big 4 or boutique)

Compensation Statement

The U.S. annual on-target earnings (OTE) range for this full-time position is between $180,000 and $220,000 USD/year. This range represents a combination of annual base pay and targeted commission. Actual offers may be higher or lower than this range based on various factors, including (but not limited to) the candidate’s work location, job-related skills, experience, and education.

DataRobot Operating Principles

Wow Our Customers
Set High Standards
Be Better Than Yesterday
Be Rigorous
Assume Positive Intent
Have the Tough Conversations
Be Better Together
Debate, Decide, Commit
Deliver Results
Overcommunicate