About Zerve
Zerve is an agentic data workspace for decision-grade data work.
Modern organisations rely on analysts, data scientists, and quantitative researchers to reduce uncertainty and recommend actions. But the tools they use today were built for exploration, not operational reasoning.
Most teams still stitch together notebooks, BI tools, orchestration systems, and scripts to move from analysis to production. This fragmentation slows decision cycles and makes reasoning difficult to reproduce, audit, or operationalize.
Zerve changes this.
Zerve enables teams to move from exploratory analysis to repeatable decision systems by combining:
- AI agents that execute data workflows
- Stateful execution environments
- Orchestration and reproducibility
- Deployable outputs like apps, APIs, and scheduled runs
Our early users include Tier 1 quantitative firms and advanced enterprise data teams using Zerve to power research workflows and agentic trading systems.
The Role
We're hiring a Solutions Engineer (Quant / Enterprise) to work closely with our most advanced users.
You'll help leading data teams adopt Zerve for real production workflows — from quantitative research environments to enterprise analytics systems.
This role sits at the intersection of:
- Engineering
- Data science
- Customer success
- Product feedback
You'll collaborate directly with both users and the core engineering team to ensure Zerve becomes a critical part of their decision infrastructure.
What You'll Do
Help customers implement real workflows
- Work directly with quantitative researchers and enterprise data teams to deploy Zerve for research pipelines, trading signal workflows, analytics automation, and decision workflows
Translate complex problems into solutions
- Understand customer workflows and design Zerve implementations that solve them effectively
- You'll often be the bridge between customer problems and Zerve capabilities
Support technical evaluations
- Help prospective customers evaluate Zerve through demos, proof-of-concept projects, architecture guidance, and workflow examples
Improve the product
- Work closely with the engineering team to surface feature gaps, performance issues, and real user needs
- Help shape the roadmap through direct exposure to advanced users
Create technical assets
- Develop reusable resources such as workflow templates, technical documentation, architecture guides, and demo projects
- These help accelerate adoption across new teams
What We're Looking For
Strong candidates typically have experience in one or more of the following:
- Data science or machine learning
- Quantitative finance or trading systems
- Distributed data infrastructure
- Developer tooling or technical platforms
You should be comfortable working with:
- Python
- Data workflows
- APIs and infrastructure tools
- Cloud environments
You enjoy working closely with users and helping them solve complex technical problems.
Nice to Have
- Experience in hedge funds or quant research environments
- Experience with data science platforms or notebook environments
- Experience deploying ML or data pipelines
- Familiarity with AI agents or orchestration systems
Why Join Zerve
You'll be helping define how organisations move from analysis to decision systems.
The next generation of AI tools will not just generate answers or code. They will power systems that continuously reason over data and drive decisions.
Zerve is building the workspace where those systems are created.
Compensation
- Competitive salary
- Meaningful equity
- Remote-first team
- Opportunity to help shape a new category of data infrastructure