The role
- COMP
- $200K - $240K
- EQUITY
- 0.10-0.25%
- LOCATION
- New York
- WORKPLACE
- On-site
- EXPERIENCE
- 3+ years
- VISA
- None, Visa transfers
- STACK
- Python, Kubernetes, AWS, GCP, Azure, Kafka, Salesforce
- INDUSTRY
- AI, Software Development, Enterprise, B2B
/roles — ROLE_186
Software Engineer (AI Platform)
Well-funded startup building an AI coding agent that lets non-engineers create secure internal software for large enterprises
The company
A well-funded enterprise AI company whose platform lets engineering, IT, and business teams generate secure internal apps with AI, with governance, access controls, and audit trails built in.
- STAGE
- growth-stage
- FUNDING
- $60M+ raised
- FOUNDED
- 2021
- BACKING
- backed by Kleiner Perkins
JD — the work
About the role
You would join a small, senior engineering team building an AI agent that writes code, so people without engineering backgrounds can create enterprise software fit for production. In close collaboration with the CTO, an early engineer at a major infrastructure software company, you would focus on making AI agents safe, accurate, and dependable in production at large scale. The company is growing quickly and is backed by top-tier venture firms and founders of well-known enterprise software companies, so early hires get significant ownership and equity upside.
What you'll do
- Build a continual learning layer with short- and long-term memory plus knowledge graphs, so the agent masters each customer's data
- Build coding agents that write, run, test, and fix code autonomously, letting non-engineers launch real apps
- Invent new ways for enterprise users to work with and correct AI agents
- Develop central governance controls that let IT teams manage apps, agents, workflows, secrets, and policies
- Solve hard problems spanning distributed systems, security, and agentic AI for a global customer base
What they're looking for
- 2+ years of software engineering experience, with 3+ preferred
- Strong backend skills in Python and cloud infrastructure such as Kubernetes, Kafka, AWS, GCP, or Azure
- Interest in AI agents and in making LLM systems reliable in production
- Drive to own large problems on a small team