GTS Global Architect - 30121

Splunk Inc; California (MO); Remote; USD 90,000 - 150,000; Full time

Job summary

An innovative company is seeking a Global Architect to drive the adoption of advanced technologies and methodologies within the Splunk ecosystem. In this pivotal role, you will collaborate with Go To Market teams, guiding clients on architecture and deployment migrations. Your expertise in machine learning and AI will be crucial as you design scalable solutions and influence product roadmaps. This is a unique opportunity to lead hands-on solutions, validate architectures, and contribute to the evolution of data strategies in a dynamic environment. If you are passionate about technology and eager to make a significant impact, this role is for you.

Qualifications

• 7+ years in technical pre-sales, services, or engineering roles.
• Deep expertise in enterprise logging, security, or observability.

Responsibilities

• Develop expertise in Splunk Platform and ecosystem technologies.
• Engage with customers to assess architecture strategies.

Skills

Enterprise Logging

Security

Observability

Machine Learning

Data Science

AI

SPL

Data Engineering

Python

Tools

Splunk

Elastic

AWS

MLTK

DSDL

Job description

Splunk Global Architects Job Description

Splunk aims to build a safer and more resilient digital world. Our platform is used by leading enterprises to ensure their digital systems are secure and reliable. We value our people highly, encouraging authenticity and passion, which makes Splunk a great place to work.

Role Overview: GTS Global Architects are experts in the Splunk platform and ecosystem. They guide Go To Market teams and customers on architecture, including cloud and deployment migrations, machine learning/AI, and data ecosystem technologies. They provide technical expertise, support pre-sales and adoption activities, and contribute to defining strategies for complex use cases. They also act as leaders and community contributors within Splunk.

This role involves collaboration across functions, researching, prototyping, and authoring strategies for designing and implementing scalable Splunk architectures. Key deliverables include guidance on complex topics, deployment patterns, and support for critical design decisions. The role is part of the Global Technical Sales Strategy and Programs organization, which is remote and distributed, reporting to the SVP of Global Technical Sales. It is a global role open to candidates in EMEA and APAC regions.

Responsibilities:

1. Develop expertise in specific capabilities such as Splunk Platform, Machine Learning, AI, and ecosystem technologies.
2. Create and deliver technical content for internal and external audiences to enable complex use-case implementation.
3. Engage with customers to assess and validate architecture strategies and use-cases, influencing product roadmaps and best practices.
4. Design validated architectures and best practices in collaboration with subject matter experts.
5. Partner with Product Management and Engineering to influence product development throughout its lifecycle.
6. Work with GTS Technical Interlock to identify customer challenges and influence product roadmaps.
7. Serve as an internal expert, answering inquiries related to your expertise area.
8. Stay updated on emerging solutions and technologies, developing collateral and guidance.
9. Lead hands-on solutions for architecture and integration needs, validating and recommending alternatives.
10. Conduct technical due diligence on partner offerings and marketplace solutions.

Qualifications:

• Deep expertise in enterprise logging, security, or observability, with experience in Splunk or similar technologies like Elastic or AWS native services.
• 7+ years in technical pre-sales, services, system administration, or engineering roles.
• 5+ years working with infrastructure and platform services supporting enterprise data challenges.
• Experience in Data Science, Machine Learning, and AI, especially with Splunk AI and apps like MLTK and DSDL.
• Hands-on knowledge of SPL and data engineering best practices for AI/ML workloads.
• Familiarity with open-source ML/AI tools, frameworks, and libraries, especially Python, and knowledge of LLMs, graph, and vector databases.
• Understanding of operational strategies for logs and metrics across various infrastructure providers.
• Experience communicating complex technical topics to diverse audiences, including executives.
• Proven track record in executing projects that help customers maximize data value.