Senior Engineering Manager, AI (FULLY REMOTE in USA)

at  Splunk

SENIOR ENGINEERING MANAGER, AI (M4)

Join us as we pursue our disruptive new vision to make machine data accessible, usable and valuable to everyone. We are a company filled with people who are passionate about our product and seek to deliver the best experience for our customers. At Splunk, we’re committed to our work, customers, having fun and most importantly to each other’s success. Learn more about Splunk careers and how you can become a part of our journey!
Role:
As the Senior Engineering Manager, AI in the Artificial Intelligence group, you will be responsible for leading the development of the core AI/ML capabilities to power the entire Splunk product portfolio and help our customers to drive their journey to digital resiliency. You will collaborate with cross-functional teams, mentor junior team members, and help drive the scientific roadmap of the area.
Responsibilities:

The responsibilities of this role include:

• Develop a long-term strategy and roadmap for integrating AI/ML technology across our product portfolio.
• Lead the development of core AI/ML models and algorithms that drive our product’s key use cases in the cybersecurity and observability domains.
• Partner with Product Leads to build a strategic product vision coupled with a flexible science/engineering plan, supporting learning through iteration.
• Stay up to date with the latest research and developments in the field of AI/ML, and ensure that these advancements are properly incorporated into our technology roadmap.
• Provide technical guidance and mentorship to team members to ensure the development of their skills.
• Develop structures to hold the team accountable for progress, for learning, for communicating, and meeting business objectives.

Requirements:

Knowledge, Skills, and Abilities:

• In-depth knowledge and proven track record in AI/ML technology, including deep learning, time series modeling, natural language processing, and unsupervised learning.
• In-depth knowledge and proven track record in Generative AI technology and Large Language Models (LLM).
• Experience with leading and managing machine learning teams of applied scientists and engineers.
• Experience with developing large-scale, complex models and deploying them in production systems.
• Experience with setting and executing innovation strategies at both technical and organizational levels to drive business objectives.
• Familiarity with architectural patterns of large, high-scale applications.
• Experience in the Cybersecurity and/or Observability industry is preferred.

Splunk is an Equal Opportunity Employer: At Splunk, we believe creating a culture of belonging isn’t just the right thing to do; it’s also the smart thing. We prioritize diversity, equity, inclusion, and belonging to ensure our employees are supported to bring their best, most authentic selves to work where they can thrive. Qualified applicants receive consideration for employment without regard to race, religion, color, national origin, ancestry, sex, gender, gender identity, gender expression, sexual orientation, marital status, age, physical or mental disability or medical condition, genetic information, veteran status, or any other consideration made unlawful by federal, state, or local laws. We consider qualified applicants with criminal histories, consistent with legal requirements.
Note:

• Develop a long-term strategy and roadmap for integrating AI/ML technology across our product portfolio.
• Lead the development of core AI/ML models and algorithms that drive our product’s key use cases in the cybersecurity and observability domains.
• Partner with Product Leads to build a strategic product vision coupled with a flexible science/engineering plan, supporting learning through iteration.
• Stay up to date with the latest research and developments in the field of AI/ML, and ensure that these advancements are properly incorporated into our technology roadmap.
• Provide technical guidance and mentorship to team members to ensure the development of their skills.
• Develop structures to hold the team accountable for progress, for learning, for communicating, and meeting business objectives