/roles — ROLE_145
Staff/Principal Software Engineer
Profitable go-to-market software company rebuilding its sales platform around AI agents
The role
- COMP
- $217K - $410K
- EQUITY
- Competitive Equity
- LOCATION
- San Francisco
- WORKPLACE
- Hybrid
- EXPERIENCE
- 8 - 15 years
- VISA
- None, Visa transfers
- STACK
- React, Ruby, Ruby on Rails, Python, MongoDB, ElasticSearch, Kubernetes, Docker, Terraform, GCP
- INDUSTRY
- AI, B2B, Data, Enterprise, Marketing, Software Development
The company
Profitable, fast-growing go-to-market platform pairing a massive B2B contact dataset with AI tools that help revenue, sales, and marketing teams find and win customers.
- STAGE
- scale-up
- FUNDING
- $250M+ raised
- TEAM
- 250+ people
- FOUNDED
- 2015
- BACKING
- backed by Sequoia, Social Capital, Y Combinator
JD — the work
About the role
You would set technical direction and own the most difficult engineering work at a profitable, fast-growing sales and marketing platform used by several hundred thousand companies, which is now reworking the whole product to be AI- and agent-first. The company wants someone with real experience running large distributed systems in production and using them to deliver products at scale, not only building the tooling. You move between top-priority projects, work closely with VPs and C-level engineering leaders, and act as the senior IC others turn to.
What you'll do
- Set the architecture for a major part of the platform, focused on distributed systems at scale or AI agent products
- Drive the toughest technical challenges, weighing build-versus-buy and cost decisions with org-wide impact
- Establish engineering patterns used across many teams and make the engineers around you more productive
- Work with product and engineering leaders to tie the technical roadmap to company goals
- Work AI-first, using coding agents to speed up investigation, design work, and building
What they're looking for
- 8+ years of software engineering, operating at staff or principal level
- A history of running large-scale distributed systems that power real products
- Deep background in distributed systems at scale, or in AI and agent products
- Comfort working directly with VPs and executive engineering leadership
- Heavy, everyday use of AI-assisted development