# Enterprise AI Architect at Distyl

- Company: Distyl
- What the company does: Architecting the AI-Native Enterprise. Distyl partners with the most ambitious enterprises to design and operationalize their AI transformations. Backed by Khosla, Lightspeed and Peak XV.
- Company website: https://distyl.ai/
- Type: Startups (AI role)
- Level: Mid level
- Location: San Francisco
- Work setup: Remote
- Pay: $200K to $275K base salary per year (USD)
- Posted: 2026-09-15
- Apply by: 2026-10-30
- Apply: https://jobs.ashbyhq.com/distyl/db39fc98-8bd3-4e63-80ce-fd5e1d244f74
- Page: https://www.1752.vc/careers/jobs/distyl-enterprise-ai-architect/

## About the role

Own the strategic technical relationship. Serve as the primary technical counterpart for strategic accounts, building trust with CIO/CTO-level leaders, enterprise architects, and business executives. Help customers identify where AI can materially change an operation, pattern-match from prior deployments, and shape an ambitious but deliverable technical vision.

## What they're looking for

- 8+ years of relevant experience across engineering, enterprise architecture, forward-deployed engineering, solutions architecture, or similar roles, with substantial customer-facing responsibility
- Hands-on production delivery experience. You have designed, built, and shipped Enterprise-grade Agentic AI/ML systems and can reason credibly about implementation tradeoffs, reliability, integration, scale, security, and operating constraints
- Demonstrated ability to operate as a senior technical advisor to executives: you can build trust, develop a point of view, shape ambiguous problems, influence decisions, and handle high-stakes technical conversations without relying on a script
- Proven ownership of complex enterprise solution architecture and scope, including the ability to write technical SOW content and align customer teams, GTM, and delivery around what is actually buildable
- Ability to work effectively with FDE / Delivery / Product & Strategy teams — bringing them in at the right time, using their current implementation depth, and maintaining continuity
- Strong working knowledge of APIs, integrations, cloud and enterprise architecture, data flows, security considerations, and modern AI systems, coding fluency to prototype, inspect systems, and engage deeply with engineers

Tags: Engineering