Manager – Engineering Operations – AI

Manager – Engineering Operations – AI

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 passion and persistence and a focus on meeting commitments.
• Self-driven and highly motivated work ethic.
• Passion for driving impact and delivering customer value through AI.

Responsibilities

• 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.
• 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.
• 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.
• 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.

Preferred Qualifications

• Background in computer science, engineering, AI/ML, or a related technical field.
• Familiarity with AI/ML tooling (e.g., SageMaker, Docker, Airflow) and big data technologies (e.g., Spark, Hadoop).
• Experience in identity governance, security, or enterprise software a plus.
• (bonus points!) Hands-on experience in AI/ML engineering, data science, or MLOps
• (bonus points!) Experience with Identity Management, Security or Governance