Senior Software Engineer at Keebo
Job details
Use AI to assess how you fit
About this role
Keebo automatically optimizes cloud data warehouses for Snowflake and Databricks to control compute costs without hurting query performance. Our platform learns each customer's workloads and adjusts warehouse settings in real time, so data teams don't have to. We're venture-backed, built on years of database and machine learning research, and fully remote. About the Opportunity We're an AI-first engineering team. We use agents across design, implementation, review, and testing, and we hold their output to the same standard as any other pull request: read it, question it, and reject it when it’s wrong. We adopt new tools and processes quickly, and we drop what isn’t working. As a Senior Software Engineer, you'll design and scale the systems behind our platform. You'll use AI to multiply your own output and the team's, and work directly with the product to turn customer problems into shipped features. You Will
Design reliable systems that process large volumes of customer warehouse data
Use AI coding tools effectively by writing clear specs and context, running agents on parallel workstreams, and reviewing their output critically
Build shared AI workflows, guardrails, and review standards that make everyone move faster
Evaluate new tools and models, and share the worthy ones with the team
Write architecture docs that explain what we're building, the tradeoffs, and why
Understand customer needs and decide what's worth building
Mentor engineers, including working effectively with AI coding tools
You Have
5+ years of software engineering experience, including time at an early-stage startup (Seed through Series B)
Deep experience with AI coding agents, and examples of how to scale their use across a team
The judgment to catch AI output that is wrong, incomplete, or risky, especially with customer data, and the habit of adapting as tools change
A track record of scaling systems as load, data, and customers grow
Strong architectural skills, with examples
Sound tradeoffs: you know when to ship something simple and when reliability, data integrity, or architecture can't wait
Proficiency in Java, Python, Go, or JavaScript/TypeScript, plus strong SQL
Experience with cloud platforms, containers, and automated deploy pipelines
Clear, collaborative communication, especially in writing: you explain what matters and why
Persistence and a constructive attitude when things break or plans change
Bonus Points
Experience with data cloud platforms. Especially Snowflake or Databricks
Experience with Angular
Experience building AI agents, agent tooling, or Model Context Protocol servers
Knowledge of query optimization, machine learning, or algorithm development
Compensation and Location The base salary is $170,000 to $200,000 for US-based candidates, plus equity. The role is fully remote and open to candidates living in the United States with authorization to work there. Visa support will not be provided. Core hours align with US Eastern Time.
What we Offer
Working with a world-class team of researchers and engineers in machine learning to turn Al algorithms into scalable and automated cloud products
For full-time positions:
Equity
Medical, dental, and vision benefits
401(k) retirement program
Home office stipend
Paid time off and paid parental leave
The latest AI tools, and freedom to try new ones
Identity Verification
We verify every candidate's identity and location through on-camera interviews, ID verification, and a background check. Equipment ships only to your verified address. Misrepresenting your identity, location, or work history ends your candidacy or employment. Keebo complies with US sanctions and export control laws.
Keebo is proud to be an equal opportunity employer and prohibits discrimination and harassment of any kind. We are committed to providing equal employment opportunities to all employees and applicants without regard to race, color, religion, sex, gender, national origin, age, disability, genetic information, or any other protected characteristic. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training. We strive to create a diverse and inclusive workplace where everyone feels valued and respected. We encourage individuals from all backgrounds to apply.
Originally posted on Himalayas