Software Engineer Product and Enablement

kausable is moving from a pure research lab toward products used by real customers. As our software engineer for product and enablement, you own two scopes, and serve two types of customers: external ones (product) and internal ones (enablement/tooling).

Product: externally shipped functionality. This is the software layer around our AI: the applications through which users interact with our AI and the delivery infrastructure that unlocks them. This entails quality assurance before and after delivery, for the technical/software axis as well as the machine-learning/capability axis.

Enablement: internal platforms and tools, developer workflows; in a sense products where the customers are your research-science colleagues.

The boundary with our ML Product Engineer is deliberate. That role owns building and improving the ML capabilties. You own the adaptable software systems through which users experience those capabilities.

Tasks

• Build customer-facing applications and integrations from scoping through delivery.
• Assure the quality of our products: before and after delivery, technical (software) and capability (machine-learning performance).
• Design APIs, workflows and frontend interfaces that keep complex model capabilities usable.
• Act as a technical bridge between researchers, product stakeholders and the people using what we build.
• Contain technical debt through thoughtful abstractions, testing and documentation.
• Design the delivery pipelines, versioning and observability needed across training, evaluation and live inference.
• Own model releases, monitoring and rollback patterns as the production footprint grows.
• Build internal platforms and tools that reduce setup time and cognitive load for researchers.
• Improve researcher experience through reproducible environments, CI/CD, automation and clear repository standards.

Requirements

• Broad software engineering experience across backend and infrastructure.
• Deep understanding of software design and complexity management: you build systems that remain easy to change.
• Strong Python skills plus TypeScript, JavaScript or another modern frontend language.
• Experience with containers, cloud infrastructure and production delivery.
• Experience with quality measurements and assurance of ML capabilities.
• A track record of customer-facing or cross-functional project work.
• Clear communication, strong problem solving and a pragmatic, self-directed operating style.
• We are primarily hiring at senior level. We are also open to exceptional candidates with fewer years of experience who can demonstrate comparable depth, judgment and ownership.

Nice to have:

• Security, privacy or on-premise deployment requirements.
• C++ or Rust for performance-sensitive services and tooling.
• Enough exposure to ML systems to collaborate productively with researchers without being expected to build models.
• Internal developer platforms, research tooling or ML infrastructure.
• Experiment tracking, data tooling or reproducible compute environments.

Benefits

Where This Can Go

You will shape how kausable builds and ships software as we scale: the architecture, tooling, standards and developer experience. The role can grow into ownership of our platform and internal engineering, or into leadership of customer-facing product delivery. The hard part is balancing both horizons: helping the team move today while keeping the system adaptable tomorrow.

Our Culture

We are "Putting Science at the Core of AI" - with all its curiosity, daringness, and humanity. That means we:

• are scientists at heart, with a builder's mindset,
• are open to challenge, grounded in curiosity and respect,
• welcome diverse perspectives and value thoughtful, open debate,
• focus on outcomes and real-world impact,
• foster an environment of support, inspiration, and freedom for everyone to do their best work.

Perks & Benefits

• VSOP equity: a real stake in what we build.
• 30 days of paid holiday per year.
• Statutory social insurance.
• Conference travel and role-relevant learning.
• Flexible hybrid work, with roughly one in-person team meet-up per month.
• A high-end laptop of your choice.

Tools and Infrastructure

• Python and a modern frontend stack.
• Docker, AWS, GCP, Hetzner, RunPod or comparable infrastructure.
• CI/CD, testing and developer-tooling systems.
• AI agents such as ChatGPT, Claude and Gemini in daily work.

Sounds like it's for you? Send us your favorite way to drink coffee along with your CV or LinkedIn, and we'll get back to you soon.

If it's a match, we'll get to know each other over a number of online interviews, followed by an onsite day where we go in depth.

We are looking forward to hearing from you!