Software Engineer AI Platform
Superblocks is an enterprise platform for building and governing AI-generated internal applications. Business teams use its Clark AI agent to build production apps on company data, while IT centrally manages integrations, authentication, access controls, security policies, and auditing.
About Superblocks
Superblocks provides a governed enterprise AI app platform for organizations that need business teams to build internal software on private enterprise data without bypassing IT controls. Its Clark AI agent generates applications, queries, and logic in natural language, while the platform provides centralized integrations, secrets management, RBAC, SSO, audit logs, version control, and deployment options including cloud, hybrid, and Cloud-Prem deployments inside customer VPCs. It serves enterprise IT, platform engineering, operations, finance, HR, marketing, and data teams, including organizations with stringent security and compliance requirements.
Skills
About the Role
You will design systems that make AI agents accurate, safe, and production-ready at scale. You will build AI memory systems, agentic code-generation and execution capabilities, and centralized governance controls. You will address challenges across agentic AI, security, sandboxing, and distributed systems.
Requirements
- Strong background in backend systems, platforms, and database design.
- Experience building agentic systems, LLM applications, or orchestration frameworks.
- Experience with security, sandboxing, or isolation in distributed systems.
- Deep intuition for model behavior, evaluation, and performance tradeoffs.
- Ability to design simple abstractions over complex AI and systems problems.
Responsibilities
- Design AI memory systems with short-term memory, persistent memory, organizational knowledge graphs, and data exploration.
- Build AI agents that generate, execute, debug, and test code.
- Handle failures and feedback so non-engineers can ship production applications.
- Build a centralized governance layer for controlling apps, workflows, users, agents, secrets, and policies.
- Define how AI agents run safely in production at global scale.
- Solve problems across agentic AI, security, and distributed systems.
