Manager, Engineering Operations - AI

SailPoint is seeking a Lead Technical Program Manager (TPM) to oversee strategic programs and lead a team of Technical Program Managers within the Product organization. This role will drive SailPoint's most complex, cross-functional programs at the intersection of AI/ML, engineering, product, and research—while also managing a high-performing TPM team.

We are looking for an experienced people leader who is deeply technical, thrives in ambiguity, and can influence across organizational boundaries. The ideal candidate has experience delivering at scale in AI/ML-driven environments, coaching TPMs, and bringing clarity and momentum to fast-paced, high-impact initiatives.

In this role, you will work at the intersection of engineering, product, and research, owning cross-functional planning, aligning stakeholders, and helping scale AI capabilities that power real customer value. You’ll partner closely with AI/ML engineers, data scientists, data engineers, product managers, and other cross-functional teams to guide programs from concept through production. This individual is passionate about cultivating relationships and has experience influencing across organizational boundaries. You will manage a program from beginning to end to ensure we’re executing successfully and delivering exceptional results. This role requires a unique blend of technical depth in AI/ML, exceptional program management skills, and a strong ability to communicate effectively with both technical and non-technical stakeholders. The ideal candidate is comfortable navigating ambiguity, thrives in complex technical domains, and brings clarity and momentum to multi-team efforts

About AI team:

The AI team at SailPoint applies AI and domain expertise to create AI solutions that solve real problems in identity governance. We believe the path to success is through meaningful customer outcomes, and we leverage traditional AI/ML as well as recent innovations in Generative AI and Graph ML to bring our solutions to SailPoint’s core product lines.

Key Responsibilities

Team Leadership & Management

• Lead and mentor a team of Technical Program Managers supporting teams across the Product organization.

• Drive performance management, career development, and operational excellence for the TPM team.

• Establish and evolve best practices, frameworks, and standards across the TPM discipline at SailPoint.

Program Strategy & Execution

• Own and drive critical AI/ML program portfolios from ideation through execution and delivery.

• Partner closely with AI/ML engineers, product managers, data scientists, and cross-functional stakeholders to deliver complex, multi-team initiatives.

• Align teams to shared goals, define success metrics, and foster a culture of accountability and continuous improvement.

Stakeholder Alignment & Communication

• Build strong, trusted relationships across Product, Engineering, Research, and Executive Leadership.

• Proactively communicate program status, risks, dependencies, and opportunities to senior leadership and cross-functional teams.

• Translate technical detail into clear and concise messaging for varied audiences.

Technical Leadership & Domain Expertise

• Use sound technical judgment and AI/ML domain knowledge to assess risks, unblock teams, and guide program direction.

• Navigate the end-to-end machine learning lifecycle (data collection, modeling, evaluation, deployment, monitoring).

• Foster cross-team collaboration and ensure scalable, high-quality solutions.

Requirements:

• 10+ years of program management experience, with at least 5 years in SaaS software and at least 2 years in ML/AI domains.

• 3+ years managing or mentoring TPMs or similar roles.

• Proven track record delivering complex, cross-functional technical programs in a fast-paced environment.

• Technical experience and knowledge of developing SaaS products - grounded in modern web technologies and agile processes.

• Strong technical acumen, able to engage in discussions about ML pipelines, data infrastructure, model deployment, or MLOps.

• Solid understanding of the end-to-end machine learning lifecycle (data ingestion, feature engineering, model training, evaluation, deployment, monitoring).

• Ability to build frameworks to track and execute program direction.

• Highly evolved EQ and ability to adapt to the needs of the program and current maturity of the teams.

• Passion for building partnerships and experience leveraging those to achieve success.

• Relentless pass