Principal Software Engineer, AI Platform

Kaicyberinc; San Jose (CA); On-site; USD 210,000 - 320,000; Full time

Benefits offered by this job

Generous compensation

Equity options

Opportunity to shape AI platform

Job summary

Kai is building an AI-powered cybersecurity platform. We seek an engineering leader for the AI platform team to set standards, design architecture, and drive scalable, reliable delivery. This is a hands-on leadership role blending coding with architecture, mentoring, and strategic decisions.

You'll partner with Head of AI and backend teams to own API contracts, testing, CI/CD, and deployment. Join a well-funded team shaping production AI at machine speed.

Qualifications

• 8+ years of professional software engineering experience with a leadership role setting standards.
• MS in Computer Science, AI, ML or related field; PhD preferred.
• Deep software architecture expertise and API contract design.
• Ownership of production systems at scale with incident response experience.
• Strong Python, clean architecture, and async patterns.
• Experience leading testing strategies for complex dependencies.
• Cloud platform expertise with Azure preferred or AWS/GCP.

Responsibilities

• Audit and roadmap: assess services, architecture, and deployment practices.
• Establish foundations: design shared library architecture and health checks.
• Define coding standards, PR reviews, and quality gates.
• Build test infrastructure and CI/CD with staging, canary, rollback.
• Own architecture decisions across AI platform and data flow.
• Lead engineering hiring for the AI team and mentor scientists.

Skills

Technical leadership

Python expert

Software architecture

Cloud architecture

Education

MS in Computer Science

PhD preferred

Tools

Azure

AWS/GCP

Job description

Kai is the AI company rebuilding cybersecurity for the machine-speed era. Founded by second time founders and trusted by Fortune 500 enterprises, Kai is building a future where security has no categories, no silos, and no human speed bottlenecks. The Kai Agentic AI Platform replaces fragmented, human-limited workflows with agentic AI systems that continuously contextualize, assess, reason, and execute security work at machine speed - making human defenders, superhuman.

Why Join Kai

Well-funded: With $125M raised, we have the capital, runway, and resolve to rebuild cybersecurity from first principles.

Proven: We've earned the trust of Fortune 500 and Global 1000 companies, and we're just getting started.

Their confidence in Kai reflects what we've built: an AI-powered cybersecurity platform that performs at the scale and speed the enterprise demands.

Experienced founders: Our founding team consists of second-time entrepreneurs, each with over 20 years of experience in the cybersecurity industry.

World-class leadership team: Our Heads of AI, Engineering, and Product bring extensive experience from some of the world’s most influential companies, ensuring top-tier mentorship, direction, and vision.

Frontier AI Applied Research Team: Our researchers operate at the leading edge of agentic AI systems, translating breakthrough capabilities into real-world cybersecurity applications.

Generous compensation: We offer highly competitive salaries, equity options, and a supportive work environment. Your contributions will be valued and rewarded as we grow together.

About the Role

We are building an AI-powered cybersecurity platform that helps enterprises manage vulnerabilities at scale. Our AI team has delivered real, working products — services that use LLMs for natural language filtering, container image analysis, package standardization, and maintenance assessment. The AI science is strong. Now, the AI team needs dedicated engineering leadership to match. You will be the technical leader of the AI platform engineering team. This is a hands‑on architecture and leadership role. You'll set the engineering standards, design the system architecture, establish the testing and deployment practices, and build the team that takes our AI services from "it works" to "it scales, it's reliable, it's maintainable, and we can ship with confidence." You'll work directly with the Head of AI, the applied AI scientists, and the backend engineering team. You'll report to engineering leadership and have a seat at the table for technical strategy decisions. This is not a management role — it's a technical leadership role where you write code, review architecture, and mentor engineers while setting the direction for how AI systems get built and operated.

Key Responsibilities

• Audit and roadmap. Assess the current services, architecture, and deployment practices. Produce an engineering roadmap that prioritizes the highest-impact improvements (we'll give you a head start — we know where the gaps are).
• Establish engineering foundations. Design and implement the shared library architecture — common patterns for configuration, DB access, error handling, structured logging, and health checks that all services adopt.
• Define the coding standards, PR review process, and quality gates.
• Build the test infrastructure. Not just write tests but design the testing strategy: how we mock LLM APIs, how we run integration tests against staging, how we measure coverage, and how it all plugs into CI. Set the standard that the team follows.
• Consolidate and fix CI/CD. You'll design a parameterized pipeline template, add test and lint stages, and establish the deployment strategy (staging, canary, rollback).
• Fix critical production issues. You'll prioritize and address the highest-risk issues while establishing patterns that prevent new ones.
• Own architecture decisions across the AI platform — API contracts, caching strategies, data flow, service boundaries, and technology choices.
• Lead the engineering hiring process for the AI team — define the roles, conduct technical interviews, and help build a high-performing team of 3-5 engineers.
• Mentor AI scientists on engineering practices — testing, code structure, version control workflows — in a way that improves their code without slowing their research velocity.
• Design evaluation and reliability frameworks for LLM-powered features — how we measure accuracy, detect regressions, and monitor production behavior.
• Partner with backend engineering to define how AI services integrate with the core cybersecurity platform — API versioning, contract testing, SLAs, and data flow.
• Translate business problems into technical architecture — work with product and AI leadership to turn ambiguous requirements into well-scoped engineering work.

Required Qualifications

• 8+ years of professional software engineering experience, with at least 2 years in a technical leadership or staff+ role where you set standards for a team or organization.
• M.S. in Computer Science, AI, Machine Learning, or a related field. PhD preferred.
• Deep software architecture expertise. You've designed shared libraries, defined API contracts, established coding standards, and made technology decisions that a team lived with for years. You think in terms of patterns, not just solutions.
• Production systems ownership at scale. You've been paged at 2am, you've run incident postmortems, you've built the monitoring that catches problems before customers do. You understand what production-grade actually means.
• Strong Python expertise with emphasis on clean architecture — dependency injection, proper module boundaries, testable design, async patterns done correctly.
• Testing leadership. You haven't just written tests — you've established testing culture. You've designed test strategies for systems with complex external dependencies.
• Cloud platform expertise. Deep experience with Azure (preferred) or AWS/GCP.