• Build and lead a best-in-class team of Data & AI Technical Architects. • Recruit and mentor senior-level architects. • Establish clear technical standards, architectural principles, and operating rhythms. • Partner with Sales Leadership to define coverage and engagement models. • Serve as a technical executive sponsor for strategic customers. • Champion customer outcomes across the full lifecycle. • Design and scale repeatable technical evaluation motions, including architectural workshops, POVs, POCs, and reference designs. • Drive alignment with Product and Engineering to stay ahead of the Data & AI roadmap. • Work closely with the Partner Ecosystem to develop offerings, use cases, and GTM strategies. • Develop scalable, reusable technical assets, patterns, and enablement. • Own Salesforce's point of view on enterprise data and AI architecture.

Job Title: Senior AI Engineer 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 Engineer, you will collaborate closely with cross-functional teams to design, develop, and deploy cutting-edge AI solutions with a focus on Generative AI and autonomous systems. This role requires a strong foundation in ML engineering, along with experience building applications with FMs and related concepts such as RAG, fine-tuning, agents, and distillation. 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 ● Deeply understand the SailPoint AI vision and Generative AI initiatives. ● Onboard onto our AI Platform tech stack. ● Develop or evaluate a working prototype of an AI agent using existing models/tools. 6 months: ● Deliver or contribute to a fully functional GenAI-powered feature. ● Optimize existing AI pipelines to ensure robust training, evaluation, and deployment. ● Collaborate with the AI and product teams to identify key use cases for GenAI. 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. Requirements: ● 5+ years experience building and deploying ML models in production at scale. ● Recent experience with Generative AI models and techniques, such as LLMs, fine-tuning, RAG, prompt engineering, guardrails, distillation, and agent frameworks. ● Can-do attitude with a focus on delivering measurable business impact. ● Strong technical communicator who can convey complex topics to different audiences. ● B.S. in Computer Science, or a related field. Tech Stack: ● Core Programming: Python, Go ● Cloud Platform: AWS (SageMaker, Bedrock) preferred ● GenAI Frameworks/Tools: Any ● Data: Snowflake, Kafka, Airflow Benefits and Compensation listed vary based on the location of your employment and the nature of your employment with SailPoint. As a part of the total compensation package, this role may be eligible for the SailPoint Corporate Bonus Plan or a role-specific commission, along with potential eligibility for equity participation. SailPoint maintains broad salary ranges for its roles to account for variations in knowledge, skills, experience, market conditions and locations, as well as reflect SailPoint’s differing products, industries, and lines of business. Candidates are typically placed into the range based on the preceding factors as well as internal peer equity. We estimate the base salary, for US-based employees, will be in this range from (min-mid-max, USD): $119,400 - $201,190.00Base salaries for employees based in other locations are competitive for the employee’s home location. Benefits Overview 1. Health and wellness coverage: Medical, dental, and vision insurance 2. Disability coverage: Short-term and long-term disability 3. Life protection: Life insurance and Accidental Death & Dismemberment (AD&D) 4. Additional life coverage options: Supplemental life insurance for employees, spouses, and children 5. Flexible spending accounts for health care, and dependent care; limited purpose flexible spending account 6. Financial security: 401(k) Savings and Investment Plan with company matching 7. Time off benefits: Flexible vacation policy 8. Holidays: 8 paid holidays annually 9. Sick leave 10. Parental support: Paid parental leave 11. Employee Assistance Program (EAP) and Care Counselors 12. Voluntary benefits: Legal Assistance, Critical Illness, Accident, Hospital Indemnity and Pet Insurance options 13. Health Savings Account (HSA) with employer contribution SailPoint is an equal opportunity employer and we welcome all qualified candidates to apply to join our team. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other category protected by applicable law. Alternative methods of applying for employment are available to individuals unable to submit an application through this site because of a disability. Contact applicationassistance@sailpoint.com or mail to 11120 Four Points Dr, Suite 100, Austin, TX 78726, to discuss reasonable accommodations. NOTE: Any unsolicited resumes sent by candidates or agencies to this email will not be considered for current openings at SailPoint.

• Lead the architecture and delivery of agentic AI solutions • Translate business problems into scalable AI architectures • Define AI governance, risk management and responsible AI controls • Advise senior client stakeholders on AI strategy, operating models and technology roadmaps • Lead, coach and develop diverse, cross-functional teams

Role Description - Design and integrate LLM-powered features, including conversational interfaces, AI agents, structured generation, and retrieval-augmented systems. - Build and maintain ML pipelines for prediction, anomaly detection, classification, and time-series analysis. - Develop backend APIs and services connecting data sources, models, and client-facing applications. - Work with structured and unstructured data across relational databases, data warehouses, and external APIs. - Optimize model performance and scalability for production environments, including monitoring and fine-tuning. - Collaborate with cross-functional teams (product, data, and engineering) to translate business requirements into technical solutions. - Ensure code quality, documentation, and best practices for deployment, testing, and maintainability. Qualifications - Strong experience with FastAPI (or equivalent async frameworks), including dependency injection, UV, Pydantic, and async/await patterns (including thread pool executors for blocking operations). - Solid understanding of REST API design, including multi-tenancy, pagination, filtering, JWT/OAuth2 authentication, and structured error handling. - Proficiency in SQLAlchemy (including async sessions), raw parameterized queries, schema design, and migrations. - Hands-on experience integrating multiple LLM providers (e.g., OpenAI, Anthropic, AWS Bedrock, Ollama, Google Gemini, Snowflake Cortex) using provider abstraction layers. - Experience with JSON response validation, markdown/code-block extraction, and fallback error handling (preferably using frameworks like Pydantic). - Knowledge of prompt engineering techniques, including context injection, temperature/token tuning, and confidence scoring. - Familiarity with embedding-based retrieval and similarity scoring. - Experience with production-grade agentic frameworks such as Pydantic AI (structured output generation, agents). - Strong experience with gradient boosting models (e.g., XGBoost, LightGBM), including GPU-accelerated training, hyperparameter tuning, and evaluation. - Expertise in segmentation, anomaly detection, and feature engineering on high-frequency sensor data. - Experience with train/test splits, feature engineering, model evaluation (R², MAE, etc.), and experiment tracking (e.g., MLflow). - Understanding of when to combine classical ML with LLM-based components (e.g., LLM-assisted labeling, embedding features in tree models). - Strong database knowledge, including complex schemas, JSONB, partitioned tables, row-level security, query optimization, and vector extensions (e.g., pgvector). - Familiarity with NoSQL databases like MongoDB and specialized databases such as Redis and Qdrant is a plus. - Experience with Snowflake (including Snowpark, Model Registry, and Cortex) or equivalent platforms. - Hands-on experience with AWS services such as Bedrock, ECS, and EC2. - Experience with Docker and CI/CD pipelines. - Familiarity with S3 or equivalent object storage solutions. - Ability to work within VPN-gated infrastructure. - Experience across multiple client environments or industries (consulting background preferred). - Exposure to Industrial IoT or sensor data (high-frequency telemetry, signal processing). - Experience in NL-to-SQL or text-to-query system design. - Ability to handle multilingual data and implement internationalization. Requirements - Strong experience with FastAPI (or equivalent async frameworks). - Solid understanding of REST API design. - Proficiency in SQLAlchemy. - Hands-on experience integrating multiple LLM providers. - Experience with JSON response validation. - Knowledge of prompt engineering techniques. - Familiarity with embedding-based retrieval. - Experience with production-grade agentic frameworks. - Strong experience with gradient boosting models. - Expertise in segmentation and anomaly detection. - Experience with train/test splits and model evaluation. - Strong database knowledge. - Familiarity with NoSQL databases. - Experience with Snowflake or equivalent platforms. - Hands-on experience with AWS services. - Experience with Docker and CI/CD pipelines. - Familiarity with S3 or equivalent object storage solutions. - Ability to work within VPN-gated infrastructure. - Experience across multiple client environments. - Exposure to Industrial IoT or sensor data. - Experience in NL-to-SQL or text-to-query system design. - Ability to handle multilingual data.