About Hyperspell

Hyperspell is the Memory & Context Layer for AI Agents.

AI agent are clueless geniuses.

AI agents are crushing humans on any standardized test, but wouldn't last a day at a real job. What today's super-intelligent agents are missing is the real world context they are operating in. A context that humans stitch together from hundreds of data points across dozens of interactions and channels. A context that grows with their tasks.

Hyperspell gives AI agents this context by connecting to their user’s workspace data and building a personalized memory and context layer.

Our Values

We believe the future is shaped by those with the boldest ideas. Our mission is to become the default context layer for all organizations that all their AI agents can connect to. We’re not doing this because it’s easy, but because it’s worth it.

We care deeply. We care about our customers and their success, about the future of AI and its contribution to society, and most of all, about each other. Building the frontier of AI, we are de facto one of the most technologically advanced companies in human history — and because of that, not despite that, want to be the most human company too. A place where we can enjoy shaping the future together.

Our Investors

We're backed by incredible investors including Y Combinator, Afore Capital, Scribble Ventures, and Pioneer Fund. Our angel investors include technical staff from OpenAI, Anthropic, xAI, and DeepMind, as well as some of the most well-respected founders in Silicon Valley, including Siqi Chen (Runway) and Julian Weisser (On Deck)

Our Founders

Hyperspell was founded in 2024 by Conor Brennan-Burke and Manu Ebert. Conor previously lead growth at Checkr and managed their $30m API product portfolio.

Manu has over 15 years of experience in machine learning and AI, sold two prior companies, led high-growth engineering teams at Airbnb, and bought his first .ai domain in 2014 (he had to send a fax (!) to the domain authority in Anguilla to do so).

About the role

As a founding product engineer at Hyperspell, your mission is to build the product surface area that makes agent memory useful, trustworthy, and easy for developers to adopt.

This is not a customer implementation role. You will talk to customers, learn from them, and build with strong user empathy, but your job is to turn those patterns into reusable product. You’ll work across the stack, with a heavy emphasis on backend systems, AI workflows, developer experience, integrations, APIs, SDKs, evals, and internal tooling.

We have a product that works, customers using it, and a category that is getting competitive quickly. The next phase is about shipping a lot of zero-to-one product, making the system work at greater scale, and building the primitives developers need to bring memory and context into their own AI workflows.

You’ll work on things like

Developer experience and SDKs
Build the APIs, SDKs, docs, examples, and integration flows that make it easy for developers to connect their applications to Hyperspell. We want integration to feel obvious, fast, and surprisingly powerful.

Agent memory primitives
Help build the product layer around context, memory, retrieval, freshness, and relevance. This may include systems for episodic memory, procedural memory, context generation, query expansion, and agent-ready summaries.

Integrations and data pipelines
Build and improve integrations across tools like Slack, Gmail, Notion, Drive, Linear, and other sources of company knowledge. Make messy data reliable, useful, and available to agents.

Product discovery through customer proximity
Talk to developers using Hyperspell, understand where they get stuck, and turn repeated pain into product improvements. The goal is not bespoke consulting. The goal is to build product that makes the next integration easier than the last one.

Zero-to-one product development
Take ambiguous product ideas from “we should probably have this” to something shipped, used, and improved. In a company this small, you’ll touch almost everything.

Requirements

• 3+ years of experience building product as a backend, full-stack, product, AI, or developer tools engineer

• Fluency in Python and TypeScript

• Strong backend engineering ability

• Experience or strong interest in AI agents, LLM systems, retrieval, memory, context engineering, or developer tools

• Strong product judgment and a bias toward shipping

• Clear communication and good user empathy

• Genuine enjoyment of building tools that help other developers succeed

• Ability to work on location in San Francisco

Compensation

• $150k-$220k base salary

• 0.5%-1.5% equity

• $10,000 to build your dream work setup

• Health, dental, and vision coverage and generous health benefits