We are looking for a Solution Engineer (FDE) to take Zipher’s autonomous execution engine into the production environments of the world’s largest data and AI organizations. You will work embedded with their engineering teams, write the code that connects Zipher to their live workloads, and own every deployment until it runs, and delivers, in production.
Our Solution Engineers work the way Forward Deployed Engineers do: as software engineers first. Whether your title today is Solutions Engineer, Forward Deployed Engineer, Solutions Architect, or tech lead, you grew up as a developer. Here, your days are spent in code — integrations, deployment tooling, and production fixes — with the customer’s architecture as your working environment.
What You’ll Do
Deploy Zipher into the customer’s production: design and build the integrations, connectors, and deployment code that plug the engine into their Databricks, Spark, Kubernetes, and AWS environments
Write production code in the field: debug live pipelines and workloads, ship fixes and extensions, and turn every one-off into a reusable building block
Own each deployment end to end — architecture, rollout, and the measured impact on cost, performance, and reliability — until the customer’s team runs it with confidence
Be the engineer enterprise teams reach for when it matters: on-call availability and responsiveness across global time zones for mission-critical production systems
Bring the field back into the product: work with core engineering and the founders to turn what you build for customers into platform capabilities
What We Offer
A product that is already winning: a new category of autonomous data platform, in production inside Fortune 500 environments, with millions of dollars in enterprise contracts already signed
An engineering seat in the field: as an FDE, you write the code, you own the deployment architecture, and what you build for customers shapes what we ship next
Engineering problems that are genuinely hard: real production data and AI workloads at enterprise scale, where every change has to hold up in front of the people who built the system
Engineers worth learning from: a deliberately talent-dense team, direct work with the founders, and a bar that pulls everyone up
Room to grow and to lead: your ownership widens as the platform does, and the people who lead moves here keep leading them
Top-of-market compensation and a meaningful equity package
The teams running the world’s largest data and AI workloads are about to stop tuning them by hand. Come be the engineer who puts it in their production. Hit Apply.
What You’ll Bring
5+ years writing production code as a software engineer — backend, full stack, or data — the foundation this role is built on
A career that grew from development toward the customer or into leadership: today a Solutions Engineer, Forward Deployed Engineer (FDE), Solutions Architect, or Customer Engineer, or a tech lead, team lead, or architect owning technical decisions other engineers built on
Strong production coding in Python or another backend language, and hands-on depth in cloud infrastructure and data platforms — AWS and Databricks, Spark, Kubernetes, or adjacent technologies
Experience building solutions directly with B2B or B2E customers, deployed into their production systems in real time
BSc in Computer Science, Electrical Engineering, or a related engineering discipline
Availability for on-call and global-hours responsiveness when an enterprise workload needs you
A high-agency, customer-obsessed engineering mindset: as comfortable in a customer’s codebase as in your own, and energized by problems nobody has solved yet
Nice to Have
Experience as a developer in an elite IDF technology unit (e.g. 8200, Mamram, Ofek, Matzpen) or another high-performance engineering environment
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 embedding complex B2B SaaS inside enterprise data, engineering, or AI teams
