Big Ideas. Real People.

At Orca, in the right environment and with the right team,talent has no boundaries. This team spirit, together with our drive to always aim high, has quickly earned us unicorn status and turned us into a global cloud security innovation leader. So if you’re ready to join an amazing team of people who inspire each other every day, now is the time to find your place in our pod.

We’re looking for driven and talented people like you to join our R&D team and our mission to change the future of cloud security. Ready to dive in and swim with our pod?

Highlights

• High-growth: Over the past seven years, we’ve consistently achieved milestones that take other companies a decade or more. During this time, we’ve significantly grown our employee base, expanded our customer reach, and rapidly advanced our product capabilities.

• Disruptive innovation: Our founders saw that traditional security didn’t work for the cloud, so they set out to carve a new path. We’re relentless pioneers who invented agentless technology and continue to be the most comprehensive and innovative cloud security company.

• Well-capitalized: With a valuation of $1.8 billion, Orca is a cybersecurity unicorn dominating the cloud security space. We’re backed by an impressive team of investors such as Capital G, ICONIQ, GGV, and SVCI, a syndicate of CISOs who invest their own money after conducting their due diligence.

• Respectful and transparent culture: Our executives pride themselves on being accessible to everyone and believe in sharing knowledge with the employees. Each employee has a place in shaping the future of our industry.

About the role

As a Senior Software Engineer - AI at Orca, you’ll design, build, and own production grade AI agents that operate at the core of Orca’s cloud security platform. You’ll work on distributed, cloud native services that embed agentic AI workflows into Orca’s existing microservices architecture.

This role goes beyond building AI logic: you’ll be responsible for operating AI systems in production, ensuring they are observable, reliable, and continuously improving through systematic evaluation and data driven iteration.

On a typical day you'll

• Design and implement cloud-native, distributed services that power Orca’s AI-driven security features

• Build and maintain agentic AI systems that reason over large-scale cloud security data and interact with multiple internal services

• Own AI agents in production, including deployment, monitoring, troubleshooting, and performance optimization

• Implement observability for AI systems, including metrics, logging, tracing, and alerting for agent behavior, quality, latency, and cost

• Develop continuous evaluation pipelines for agentic solutions, including offline testing, regression detection, and production feedback loops

• Design and optimize RAG pipelines that operate reliably over high-volume, high-variance security data

• Apply strong software engineering practices: clear APIs, clean abstractions, robust error handling, and scalable data flows

• Lead services end to end - from design and implementation to deployment and long-term operation

• Collaborate closely with Data Platform, Product, and Security Research teams to ensure AI behavior is correct, explainable, and trustworthy

About you

• 5+ years of professional software engineering experience building and operating production systems

• Strong proficiency in Python & Typescript and experience designing backend services

• Solid experience building cloud-native, distributed systems in a microservices architecture

• Hands-on experience building, deploying, and maintaining AI systems in production

• Proven hands-on experience building AI systems using LLM and agentic frameworks in production

• Practical experience with agentic AI workflows, including tool use, multi-step reasoning, and orchestration

• Experience implementing observability and monitoring for complex systems (metrics, logs, traces)

• Experience designing or working with evaluation frameworks for AI systems (quality, drift, latency, cost)

• Ability to reason about tradeoffs and continuously improve systems based on real-world data

Big advantage

• Experience evaluating AI systems in high-stakes domains (security, reliability, correctness)

• Background in cloud security, cybersecurity, or large-scale SaaS platforms

• Familiarity with RAG evaluation techniques, prompt versioning, and regression testing

• Experience operating AI-enabled services at scale in AWS or similar cloud environments