Principal AI Systems Engineer (Agentic Platforms)

• You will define and evolve the architectural foundations of Kindo’s agent platform
• This is applied systems engineering at the frontier of AI-native development, not ML research and not chatbot wrappers
• You’ll work on agent execution frameworks, memory architectures, multi-model execution, secure tool-calling integrations, and the platform primitives that determine what autonomous systems can reliably do
• This role requires invention and unusually strong technical judgment. Many of the paradigms for agentic systems are still emerging
• You’ll continuously track the ecosystem, explore new approaches, prototype quickly, and decide what becomes the platform’s durable foundation
• You will identify the highest-leverage architectural opportunities, the failure modes most likely to bite us, and the guardrails and abstractions that let the system scale safely
• Principal engineers at Kindo are builders and inventors who help determine what the future of agentic systems should look like, while ensuring the platform remains reliable, secure, observable, debuggable, and maintainable under real-world conditions
• Agent execution architectures, including autonomous task loops, scheduling, triggers, control planes, and failure isolation
• Retrieval and memory architectures, including persistent, structured, and contextual memory systems
• Multi-model routing and orchestration across providers, balancing quality, latency, cost, and failure modes
• Tool-calling and integration frameworks for safe interaction with external services and enterprise environments
• Reliability, security, and operability foundations, including evaluation, observability, auditing, and recovery paths
• Core platform primitives and architectural patterns that enable entirely new autonomous capabilities safely
• AI is a first-class tool in how we engineer. You use AI across design, prototyping, implementation, testing, debugging, and incident response, and you continuously refine workflows that increase leverage without sacrificing quality
• At this level, you also help define the engineering paradigm itself: how we use autonomous agents and AI-driven workflows to compound velocity over time while minimizing slop, security risk, and architectural drift
• You build with discipline. You create boundaries, verification strategies, and operational guardrails so systems remain understandable and controllable as autonomy increases. You ensure the platform can evolve rapidly without losing reliability and security

Benefits

• Unlimited vacation and paid time off policies
• Comprehensive health, dental, and vision insurance
• Equity package- TypeScript required, Python strongly preferred
• Demonstrate exceptional architectural judgment around reliability, security, observability, and long-term system evolution
• Have built LLM-powered or AI-native systems beyond demos, with real users, constraints, and failure modes
• Domain familiarity with DevOps, SecOps, or infrastructure automation is a plus
• Have built and evolved platform-level architectures that remained durable under rapid change
• Have deep expertise designing and operating complex backend or distributed systems in production
• Experience with production infrastructure; Docker/Kubernetes experience is a plus
• Have invented or introduced foundational abstractions, workflows, or architectural approaches that materially improved system capability or engineering effectiveness
• Strong SQL proficiency
• Use AI as a core part of your engineering workflow, not as an occasional convenience
• Familiarity with enterprise security patterns is a plus
• Actively track emerging tools, models, and approaches and translate the best of them into production systems
• Operate with exceptional ownership and take systems end-to-end, including long-term evolution- Send us:
• Your work. A portfolio, demo, GitHub profile, blog post, recorded walkthrough, or any evidence of AI systems you’ve built. We want to see how you think, not just what you’ve done
• A brief note on what excites you about agentic systems and where you think the hard problems are
• Your resume, but know that the first two items matter more
• We’ll move fast. The interview process is designed to see how you actually work, not quiz you on trivia