Job description

ABOUT BLOCKIT Time is the the most valuable resource we have, yet coordinating it remains stuck in the dark ages. At Blockit, we're building the AI that finally fixes this: an autonomous time agent that handles the full complexity of scheduling—timezones, group coordination, in-person logistics—like an executive assistant that never sleeps. While every LLM application to date has been a one-on-one conversation, Blockit is one of the first multiplayer, stateful AI agents—coordinating between multiple people, maintaining context across conversations, and taking real actions in the world. As more people connect their calendars, our network becomes exponentially more powerful. This is the foundation of a platform of AI agents with access to the world's time. We're backed by Sequoia, and we're a small, sharp team that moves fast, ships constantly, and holds a high bar. If you want to build something genuinely new, we'd love to talk. You can visit our teams page notion.so to learn more about our team and culture! THE ROLE You’ll own the intelligence at the core of Blockit: our scheduling agents that autonomously coordinate meetings across people, time zones, and constraints. This includes designing and iterating on agent architectures, writing and refining prompts, building evaluation frameworks, and shipping new capabilities as models improve. You’ll work across our orchestrator agents (which manage conversation flow) and specialized sub-agents, with the goal of making Blockit smarter, faster, and capable of handling increasingly complex coordination problems. You’ll be architecting and building real-world AI agents used in production. WHAT YOU’LL DO - Write and refine prompts across our agent system—orchestrators, sub-agents, and tools - Build and maintain evals to measure agent quality and catch regressions - Debug agent failures: figure out why it misunderstood a request or made a bad call - Implement new agent capabilities as user needs expand - Experiment with new architectures and techniques as models improve - Instrument and analyze agent behavior to find patterns and failure modes WHAT WE’RE LOOKING FOR - 2+ years of experience shipping and owning production software - Strong backend engineering skills, with the ability to work across the stack when needed - Experience working with LLMs in production systems (or a demonstrated ability to learn quickly in this space) - Deep curiosity about agent architectures and how the industry is evolving beyond simple prompt-based systems - Clear, structured communicator who can explain what’s working, what isn’t, and why LOCATION - San Francisco, CA. On‑site 4 days per week

Requirements

Must-haves

You’ll own the intelligence at the core of Blockit: our scheduling agents that autonomously coordinate meetings across people, time zones, and constraints.
You’ll be architecting and building real-world AI agents used in production.
Write and refine prompts across our agent system—orchestrators, sub-agents, and tools
Build and maintain evals to measure agent quality and catch regressions
Debug agent failures: figure out why it misunderstood a request or made a bad call
Implement new agent capabilities as user needs expand
Experiment with new architectures and techniques as models improve
Instrument and analyze agent behavior to find patterns and failure modes
2+ years of experience shipping and owning production software
Strong backend engineering skills, with the ability to work across the stack when needed
Experience working with LLMs in production systems (or a demonstrated ability to learn quickly in this space)
Deep curiosity about agent architectures and how the industry is evolving beyond simple prompt-based systems
Clear, structured communicator who can explain what’s working, what isn’t, and why
San Francisco, CA. On‑site 4 days per week

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

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