Description
Responsibilities:
- Develop and maintain deep competencies in specific capabilities areas needed by Splunk customers (e.g. Splunk Platform, Machine Learning and AI, and ecosystem technologies)
- Develop and deliver technical content to internal and external audiences to enable and empower customers and Splunkers on complex use-cases
- Foster customer initiatives for AI using indexed data and existing toolsets, e.g. Splunk Machine Learning Toolkit (MLTK), Splunk App for Data Science and Deep Learning (DSDL)
- Engage with customers to assess and validate complex use-cases and direct them to realizing successful use cases
- Work with key customer leads on the AI strategies for security and observability, identifying alignment to Splunk’s increasing advance Product offerings
- Partner with Product Management and engineering on thematic needs of customers, to optimize existing AI use cases and address new use cases
- Design Splunk Validated Architectures and best practices in cross-functional partnership with subject matter experts across Splunk
- Partner with Splunk AI Product and engineering to share customer learnings, influence Splunk’s product roadmap
- Act as an internal technical expert, fielding inquiries from a Global audience related to your area of subject matter expertise (ML/AI)
- Become an expert on soon-to-be-released solutions, capabilities and emerging ecosystem technologies in your competency areas. Use your expertise to develop use-cases collateral and technical guidance
- Provide hands-on leadership to solve Splunk technical architecture/integration needs, proactively validating, defining alternatives, and making recommendations to Product
- Provide technical due diligence for assessing offerings from partners and the marketplace
Qualifications:
- Possess a depth of expertise in enterprise logging, security and/or observability, specifically utilizing Splunk and/or other aligned technologies and solutions (e.g. Elastic, AWS native services, etc.)
- 7+ years of experience in technical pre-sales, services, system administration, and/or engineer roles
- 5+ years of experience working with infrastructure and platform services to support enterprise-scale data challenges
- An excellent depth of experience and hands-on knowledge in Data Science, Machine Learning and AI methods, tools and technologies, preferably related to Splunk AI and its key apps (e.g. MLTK, DSDL).
- Experienced hands-on working knowledge about SPL and data engineering best practices in Splunk to prepare data for AI/ML workloads.
- Experience with open source ML/AI tools, frameworks and libraries, especially in python. Coding skills and knowledge about LLMs, graph and vector databases or integration with 3rd party AI services is a plus.
- Knowledge of strategies for operationalizing logs and/or metrics across infrastructure providers (i.e. on-premises, Amazon Web Services, Azure, and/or Google Cloud Platform
- Experience presenting complex technical topics to all audiences, from working-level administrators to executive stakeholders
- Demonstrated expertise in the execution of projects and deliverables to support technology customers’ understanding and ability to capture the full value of their data investments
Note:
Base Pay Range: $181,200.00 - 249,150.00 per year
Base Pay Range: $163,080.00 - 224,235.00 per year
Base Pay Range: $144,960.00 - 199,320.00 per year
Thank you for your interest in Splunk!
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