over 2 years ago
Remote, United StatesSenior
Responsibilities
- Build new features across the stack, including backend logic, APIs, and polished UI components.
- Design and iterate on AI-powered chatbots, copilots, code-generation tools, and agents.
- Use prompts, evaluations, and context handling to deliver reliable AI features.
- Enhance the real-time collaborative notebook experience.
- Structure, transform, and route information through the product with a data-first approach.
- Gather user feedback, design comprehensive workflows, and support the data science and developer community.
- Own projects end to end, from initiative and planning through delivery and tracking.
Requirements
- Strong full-stack product engineering skills with TypeScript, React, Node.js, GraphQL, and PostgreSQL.
- Hands-on experience with AI/LLM products such as chatbots, assistants, or other AI-powered features.
- Comfort designing prompts, interacting with AI models, and optimizing AI experiences.
- Understanding of LLM tokenization, memory and context limits, and cost, latency, and quality trade-offs.
- A data-oriented mindset and ability to reason practically about information flow through a product.
- Ability to learn and ship quickly, take ownership, and work proactively and creatively.
- Experience using Cursor, Claude Code, or an equivalent parallelized agentic coding tool.
Benefits
- Competitive compensation package and equity options.
- Team events, off-sites, and company retreats.
- Unlimited-budget credit card for learning, self-development, and work-related expenses.
- Travel budget to meet the team.
- 25 days of PTO and unlimited sick days.
- Paid parental and family leave.
- Flexible working hours.
- $2,000 kick-start bonus and $1,000 health budget.
- Paid lunches, snacks, and drinks as an office benefit.
- Super cool company swag.
Tech Stack
Categories
About Deepnote
Deepnote builds a collaborative, cloud-based data notebook for data scientists and analysts, combining SQL, Python, and visualizations with Jupyter compatibility. Teams use it to explore data, connect to warehouses like BigQuery or Snowflake, schedule runs, and publish dashboards or apps; it is sold as a SaaS subscription. Founded in 2019 and headquartered in San Francisco, the company is privately held and raised a Series A in 2022.