Partner Solutions Architect - Public Sector

• 2+ years e in technology solutions, practice development, architecture, consulting and/or cloud/infrastructure technologies.
• Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field, or equivalent practical experience.
• 1+ years of pre-sales experience in the software sector, ideally partner-facing: channel, alliances, SI/GSI or MSSP ecosystems in the US Public Sector.
• A one-to-many mindset: you would rather teach ten engineers to run the demo than run it ten times yourself, and you can show where your enablement turned into someone else's win.
• Working knowledge of security operations (SIEM, endpoint, cloud security) and/or observability, plus an understanding of AI and semantic search technologies.
• Professional experience architecting or operating solutions on AWS, Google Cloud or Microsoft Azure.
• Commercial fluency: you can read a deal, discuss services scope and margin with a partner, and translate technical capability into the business case their customer buys.
• Excellent communication and presentation skills for technical and non-technical audiences
• Comfort with ambiguity and a self-starter's bias to action; you inspire partner teams to work on what is most relevant, not just what is urgent.
• Demonstrated ability to stay focused and deliver results amid ambiguity, distractions, and competing priorities.
• Comfortable operating both collaboratively across partner and cross-functional teams and independently to execute a plan and deliver results
• Skilled at leading through influence, aligning partners and internal stakeholders around shared priorities and goals
• Technical experience in at least one Elastic solution area is highly desired (AI agents & Search, security operations, or observability); cross-domain fluency across all three is a differentiator
• Must be able to travel to partner offices, events, and conferences in support of partner activities; approximately 30% travel expected
• Must be located in or within reasonable commuting distance of the Florida Panhandle (e.g., Pensacolarea or be willing to immediately relocate

Bonus Points

• Meaningful, demonstratable, experience with AI/ML technologies, including exposure to LLMs, embeddings, vector search, or agentic AI frameworks
• Proficiency in at least one scripting or programming language (Python, Bash, or similar) for automation, integration, or demonstration purposes
• Prior experience in a technical training, instruction, or curriculum development capacity is a plus

Compensation for this role is in the form of base salary plus a variable component, that together comprise the On-Target Earnings (OTE). On-Target Earnings (OTE) are based on a 70/30 pay mix (base salary / target variable).

The typical starting OTE range for new hires in this role is listed below. This range represents the lowest to highest OTE we reasonably and in good faith believe we would pay for this role at the time of this posting. We may ultimately pay more or less than the posted range, and the range may be modified in the future.

An employee's position within the OTE range will be based on several factors including, but not limited to, relevant education, qualifications, certifications, experience, skills, geographic location, performance, and business or organizational needs.

Elastic believes that employees should have the opportunity to share in the value that we create together for our shareholders. Therefore, in addition to cash compensation, this role is currently eligible to participate in Elastic's stock program. Our total rewards package also includes a company-matched 401k with dollar-for-dollar matching up to 6% of eligible earnings, along with a range of other benefits offered with a holistic emphasis on employee well-being.

The typical starting salary range for this role is:

$74,700—$118,100 USD

The typical starting Target Variable range for this role is:

$32,000—$50,600 USD

The typical starting On-Target Earnings (OTE) range for this role is:

$106,700—$168,700 USD