Staff Platform Engineer - Infrastructure

About Kalepa:

Insurance is a $7T global industry built on professional labor: underwriting, claims, pricing, operations, and distribution. Kalepa is building AI that can perform that work.

We create professional-grade AI systems for insurers: software that can read, reason, decide, and act inside real workflows and operate over long-time horizons. Kalepa begins by augmenting professionals with the tools to succeed at their jobs. That earns us the right to learn from real decisions, capture decision traces, and automate what can be automated successfully over time.

Our products are already in production with leading insurers, driving measurable outcomes and expanding across functions. The opportunity is far broader than any single workflow: to build the AI operating system for decision-making across insurance. For people who want to work on AI that matters, in a sector where correctness, trust, and real-world impact count, Kalepa is just getting started.

Kalepa is backed by leading investors such as IA Ventures and Inspired Capital, and our team brings experience from Facebook, Palantir, Google, Amazon, McKinsey, Mastercard, and Uber.

Kalepa’s culture isn’t for everyone, and that’s ok. But for the people who are a fit, they can’t imagine working elsewhere.

About the role

Salary range: 220k – 300k USD Location: Remote (USA)

We are looking for smart engineers who love to code, seek challenging problems, and appreciate recognition for excellent work. As part of the infrastructure team, you will work on the infrastructure and tooling that power our core platform. You’ll maintain CI/CD pipelines, automate operational workflows, and ensure we stay secure and compliant to the industry standards. Your day-to-day responsibilities will include improving infrastructure performance and reliability, monitoring and optimizing system cost, and collaborating with engineering teams to standardize environments and deployment patterns. You’ll help to maintain observability and incident response processes, and ensure the scalability of our cloud-based systems as we continue to grow.

You'll collaborate with a global team of full-stack, data, AI, and DevOps engineers to build scalable backend solutions as we continue to grow. We're a small team where individual contributions have an outsized impact on both our technology and our business.

You'll be right at home if you:

• Have 8+ years of software engineering or DevOps experience, ideally with time spent working on infrastructure, performance, security, or compliance.
• You're excellent at your craft and relentless in pursuing it.
• Take full ownership of your work and drive projects to completion with minimal oversight.
• Communicate proactively, surfacing blockers, asking the right questions, keeping stakeholders in the loop.
• Thrive on experimentation: you're comfortable testing ideas, measuring results, and iterating quickly on problems no one has solved before.
• Have strong fundamentals in system design, debugging, and problem-solving.
• Know Python (our main stack), though we're open to strong candidates from other OO backgrounds.
• Have experience with serverless technologies (Lambda, EC2), asynchronous workflows, and cloud environments.
• Have strong knowledge of relational databases and their performance tuning, ideally PostgreSQL.
• Know terraform, IaaC best practices, Docker or similar tools.
• Bonus: experience with LLMs/generative AI, distributed systems

What you’ll get:

• Competitive salary (based on experience level).
• Significant equity options package.
• Work with an ambitious, smart, global, and fun team to transform a $7T global industry.
• 20 days of PTO a year.
• Global team offsites (2024 - Lisbon, 2025 - Cartagena).
• 100% covered medical, 100% covered vision and dental for individuals and families.
• Healthy living/gym stipend. Mobile phone bill stipend.
• Continuing education credits.
• 401(k) plan with employer contribution (regardless of employee contribution)

The salary range listed is an estimate and will vary based on a variety of factors. Final compensation will be determined during the offer stage based on relevant experience, performance during the interview process, and geographic location, and may therefore differ from the posted range.