AI Systems Engineer

Engineering at hyperexponential

At hyperexponential (hx) we are transforming the traditional insurance industry with our groundbreaking SaaS platform, hx Renew. Insurers use it to build complex mathematical models that enable smarter, faster pricing decisions—whether it’s calculating the cost to insure a global superstar’s concert tour or protecting entire states from natural disasters.

With hx Renew, insurers can rapidly develop and iterate pricing models in Python and React within a modern software environment, free from the burden of legacy tech. What once took months now takes weeks—or even days. This agility has made our product the go-to platform for insurers worldwide.

In just five years, our winning formula has earned the trust of industry giants like Aviva and Top 5 US insurers, as well as cutting-edge innovators like Convex and Inigo. Our engineering team—made up of some of the brightest (and kindest!) minds in the industry—pushes technological boundaries every day through creative innovation and regular hackathons.

Your Mission

We're expanding our Engineering Velocity team with a brand new role focused on AI enablement. Our mission is simple: empower engineers to deliver better, faster, and safer.

Over the past months, we’ve been exploring how AI can improve developer workflows. We've integrated tools like Codeium and Windsurf IDE, and we're currently evaluating AI-powered solutions for code reviews. But we know there’s more we can do—and that’s where your expertise and enthusiasm come into play.

We’re looking for someone excited about applying AI to improve the developer experience—whether through automation, smarter tooling, or rethinking how engineers work. You’ll help us go beyond off-the-shelf tools and lead new initiatives that accelerate how engineers build, ship, and operate software at hx.

Key Responsibilities

• Lead AI-driven initiatives: Identify opportunities to apply AI in meaningful ways that improve how engineers work, automating repetitive tasks, accelerating decision-making, and improving productivity.
• Shape AI adoption at hx: As the person leading this effort, you’ll define the approach to incorporating AI into engineering workflows, helping us discover and implement the best AI tools and techniques that will drive real impact.
• Collaborate and share knowledge: Make AI accessible to your teammates by sharing knowledge, fostering a culture of learning, and empowering others to contribute to AI-driven projects. You'll help others grow their skills and contribute to AI initiatives.
• Push the boundaries of what's possible: Always be on the lookout for ways AI can make us faster, more efficient, and more effective. You’ll tackle challenges and find creative solutions that shape the direction of AI within the technology department.

Key Skills and Experience

• Proven problem solver: Proven experience building internal tooling and platforms to support engineering teams
• Experience with AI technologies: Hands-on experience working with LLMs or related AI technologies, with a practical understanding of how to apply them effectively to real-world developer workflows.
• Solid technical foundation: Strong experience in DevOps practices with hands-on knowledge of cloud technologies (AWS), infrastructure as code (Terraform), CI/CD pipelines (GitLab), and containerization (Docker).
• Strong Python programming skills: Strong programming skills in Python, including its ecosystem for AI/ML, with experience using libraries such as PyTorch, Hugging Face Transformers, scikit-learn, and TensorFlow to build and implement AI-driven solutions.
• Product mindset: Ability to think from the user’s perspective and design solutions that align with developer needs, improving their experience and productivity.
• Leadership and ownership: Experience taking ownership of projects, leading initiatives from inception to delivery, and driving impactful results that align with team and business goals.
• Excellent communication and collaboration skills: Ability to clearly explain complex technical concepts to both technical and non-technical stakeholders, empowering teammates to get involved and contribute to AI-driven initiatives.

Interview Process

Initial chat with our Talent team to kick things off

• Manager Interview (60 minutes)
• Technical Assessment (120 minutes)
• Values Interview
• We offer!