Solutions Engineer

Zipher is building the Autonomous Execution Layer for cloud data and AI workloads. Backed by $50M in funding, we dynamically orchestrate clusters, predict bottlenecks, and auto-heal infrastructure in real time — with zero human intervention. Our platform runs in production at global enterprise customers, including Fortune 500 companies, delivering mission-critical resilience and sub-second optimization.

Autonomous execution is a new category, and we are the ones defining it — already running in production inside Fortune 500 environments, where being wrong is not an option. The team is small and deliberately talent-dense; every hire changes what we are able to build next.

We are looking for a Solutions Engineer to be the technical face of Zipher in front of the world’s largest data and AI organizations. You will sit with the engineers who run those environments, prove what autonomous execution does to their cost, performance, and reliability, and turn what you learn in the field into what we build next.

What You’ll Do

• Own the technical win end to end: discovery, solution architecture, and the case that convinces senior engineering and data leaders
• Run proof-of-value engagements on customers’ own telemetry and real workloads — measured results, not slideware
• Quantify Zipher’s impact in the numbers the customer already trusts: cloud cost, SLA, workload efficiency, and reliability
• Be the trusted technical voice on Databricks, cloud infrastructure, and workload orchestration for teams running mission-critical production systems
• Bring the field back into the building: shape roadmap, integrations, and enterprise capabilities with what only you see
  
  

• Own the technical customer journey for a category we are defining, not competing in
• High ownership from day one: direct exposure to founders, and field insight that changes the product within weeks
• A small, deeply technical team where the bar is the point — we hire slowly and expect a lot
• Top-of-market compensation and meaningful equity
  
  

• 5+ years in Solutions Engineering, Sales Engineering, or technical consulting, owning technical evaluations that decided real deals
• Genuine hands-on depth in cloud infrastructure and data platforms — AWS and Databricks, Spark, Kubernetes, or adjacent technologies
• The ability to hold a room of senior engineers and executives and translate complex architecture into outcomes both of them care about
• Command of technical workshops, demos, whiteboarding, and POCs as your default way of working
• A high-agency, customer-obsessed mindset: curious, structured, technically rigorous, and energized by problems nobody has solved yet
  
  

• Experience with Databricks, Apache Spark, Snowflake, Airflow, dbt, Kubernetes, or cloud-native data platforms
• Background in cloud cost optimization, FinOps, platform engineering, SRE, or data engineering
• Experience deploying complex B2B SaaS into enterprise data, engineering, or AI teams
• Experience in an elite IDF technology/intelligence unit or another high-performance technical environment