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
What We Offer
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
The teams running the world’s largest data and AI workloads are about to stop tuning them by hand. Come be the person who shows them what that looks like. Hit Apply.
What You’ll Bring
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
Nice to Have
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
