AI Engineering Manager

About SailPoint: 

SailPoint is the leader in identity security for the cloud enterprise. Our identity security solutions secure and enable thousands of companies worldwide, giving our customers unmatched visibility into the entirety of their digital workforce and ensuring that workers have the right access to do their job—no more and no less. 

Built on a foundation of AI and ML, our Identity Security Cloud Platform delivers the right level of access to the right identities and resources at the right time—matching the scale, velocity, and changing needs of today’s cloud-oriented, modern enterprise. 

About the role: 

As an AI Engineering Manager, you will lead a high-performing engineering team responsible for building the next generation of SailPoint’s agentic and Generative AI capabilities. Your team will design, develop, and operationalize frameworks, SDKs, and evaluation pipelines that enable scalable agent development across the company. You will also lead the development of the agents themselves. 

You will balance technical leadership, people management, and delivery ownership, ensuring your team builds robust, maintainable systems while partnering closely with other AI and product domain engineering teams. You will help define our AI engineering standards, scale the AI development lifecycle, and foster a strong culture of innovation, quality, and accountability. 

About the 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. 

Roadmap to success: 

90 Days 

• Develop a deep understanding of SailPoint’s AI and agentic vision, platform architecture, and development workflows. 

• Build relationships with product, platform, and engineering stakeholders to understand priorities and dependencies. 

• Assess team capabilities and processes and implement improvements. 

• Guide delivery of an AI agent or GenAI-powered feature, ensuring high engineering standards and production readiness. 

6 months: 
 

• Establish clear team operating mechanisms around architecture reviews, evaluation standards, and experimentation workflows. 

• Partner with AI Platform to evolve agent orchestration, memory/state management, tool integration, and evaluation pipelines. 

• Hire, coach, and develop engineers. Identify growth paths and delegate ownership effectively. 

1 year: 
 

• Lead the development of a new FM-based capability from ideation to deployment.  

• Drive AI innovation by rapidly incorporating advancements in FM fine-tuning, prompt engineering, agent-based systems, etc. into our product and platform.  

• Establish repeatable frameworks for evaluating GenAI and agent-based features in production, emphasizing business impact and risk mitigation.  

• Collaborate with partners to deliver thoughtful integrations between traditional ML and agent-based systems that provide a seamless and autonomous user experience.  

• Manage team resources, including budget and personnel, to ensure efficient project execution.  

Responsibilities:  
 

• Lead and manage a team of AI Engineers, providing technical guidance and mentorship.  

• Oversee the design, development, and deployment of AI solutions, ensuring alignment with business goals and product roadmaps.  

• Drive the adoption of best practices for AI development, including coding standards, testing, and deployment processes.  

• Collaborate with cross-functional teams, including product management, engineering, and research, to define and prioritize AI initiatives.  

• Stay up-to-date with the latest advancements in AI and ML, and evaluate new technologies and frameworks for potential use at SailPoint.  

• Foster a culture of innovation and collaboration within the AI team, encouraging experimentation and knowledge sharing.  

• Ensure the delivery of high-quality AI solutions that meet performance, scalability, and security requirements.  

• Contribute to the overarching architecture and best practices for agent development, ensuring reusable components and a centralized vision as the field evolves.  

• Work on a variety of projects that are among the company’s top priorities, with a mix of direct building and cross-team enablement.  

• Manage project timelines and resources, ensuring on-time and within-budget delivery. 

Requirements: 

• 7+ years of experience developing and scaling enterprise-grade software products. 

• Track record as a Tech Lead or Architect driving cross-functional initiatives and mentoring engineers across domains. 

• Deep experience building agentic frameworks or LLM-based applications, including tool orchestration, memory/state management, and evaluation pipelines. 

• Strong engineering fundamentals—API design, distributed systems, observability, CI/CD, and secure deployment at scale. 

• Proven ability to define and propagate AI development standards and best practices across an organization. 

• Exceptional communication and collaboration skills; capable of influencing architecture and strategy across product and platform teams. 

Preferred Qualifications 
 

• Previous experience managing a team of AI Engineers or ML Engineers. 

• Experience with building microservices in AWS. 

• Understanding the challenges of building data pipelines for AI features. 
   

Tech Stack: 

• Core Programming: Python, Go 

• Cloud Platform: AWS (SageMaker, Bedrock) preferred 

• GenAI Frameworks/Tools: MCP/A2A/LangGraph or similar 

• Data: Snowflake, Kafka, Airflow 

Remote Work and Time Zones: