GTS Global Solution Architect (ML/AI)
Description
GTS Global Architects are a distributed, remote team of Splunk platform and ecosystem domain experts. Global Architects guide Go To Market teams and customers on Splunk Architecture, inclusive of Cloud and customer-managed deployment expansions and/or migrations, machine learning/AI and machine data ecosystem technologies.
Splunk provides Machine Learning (ML) and Artificial Intelligence (AI) capabilities throughout the entire product portfolio. Splunk has developed and embedded pre-built AI/ML features directly within premium products, such as Splunk Enterprise Security and Splunk IT Service Intelligence, which have been designed to apply AI/ML to specific high-demand use cases. In addition, Splunk’s flexible data platform allows users to build custom AI/ML solutions to achieve outcomes, beyond what is provided out-of-the-box allowing organizations to address bespoke AI/ML requirements.
Global Architects for this role provide deep-technical expertise and are key contributors to defining pre-sales and adoption activities to support large and complex ML and AI use-cases. Global Architects spend the majority of their time on projects and deliverables that directly relate to and impact customer demand, adoption or understanding of Splunk solutions, such as internal guidance to technical sellers, advocacy for critical Product design decisions, or external guidance such as deployment patterns, research, prototypes, and assisting with customer proof of concepts for production use-cases of Splunk.
Global Architects collaborate cross-functionally, and partner with regional Architects and account teams in support of key customers, and leading engagements specific to architecture initiatives and validation of complex use-cases.
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.)
- 5+ years of experience in technical pre-sales, services, system administration, and/or engineer roles
- 4+ years of experience working with infrastructure and platform services to support enterprise-scale data challenges
- A good 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 senior 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
Australia
Base Pay: AUD 140,000.00 - 192,500.00 per year
Splunk provides flexibility and choice in the working arrangement for most roles, including remote and/or in-office roles. We have a market-based pay structure which varies by location. Please note that the base pay range is a guideline and for candidates who receive an offer, the base pay will vary based on factors such as work location as set out above, as well as the knowledge, skills and experience of the candidate. In addition to base pay, this role is eligible for incentive compensation and may be eligible for equity or long-term cash awards.
Benefits are an important part of Splunk's Total Rewards package. This role is eligible for a comprehensive, competitive benefits package which may include healthcare and retirement plans, paid time off, wellbeing expense reimbursement, and much more! Learn more about our comprehensive benefits and wellbeing offering at https://splunkbenefits.com.
Thank you for your interest in Splunk!