AI ENGINEER @ MANIFEST IT
Manifest is a Sequoia-backed stealth startup building the operational memory layer for autonomous engineering, moving beyond code generation to handle infrastructure across teams and providers. We are currently building an intelligence layer on top of our infrastructure graph to transform change data into reasoning, risk detection, and agent-native systems. As an AI Engineer, you will work at the intersection of infrastructure intelligence and AI agents, contributing to a platform that spans design and runtime for enterprise customers.
In this role, you will design and deploy agentic systems that reason over live infrastructure graphs, focusing on risk prediction and causal chains. You will be responsible for translating cutting-edge LLM research into practical product features, especially for coding agents that require grounded infrastructure context. We operate in a fast-paced, stealth environment and require our team to work in-office five days a week in San Francisco to ensure rapid iteration and collaboration based on real-time customer feedback.
In this role, you will design and deploy agentic systems that reason over live infrastructure graphs, focusing on risk prediction and causal chains. You will be responsible for translating cutting-edge LLM research into practical product features, especially for coding agents that require grounded infrastructure context. We operate in a fast-paced, stealth environment and require our team to work in-office five days a week in San Francisco to ensure rapid iteration and collaboration based on real-time customer feedback.
Key Requirements
2+ years hands-on AI/ML engineering experience
A Bachelor's or Master's degree in Computer Science or a related field
Strong experience applying LLMs to complex problems like infra, DevOps, or developer tooling
Demonstrated ability to work effectively in early-stage, ambiguous environments
Clear communication skills for both technical and customer-facing contexts
Willingness to work in-office 5 days a week in San Francisco
Experience designing and deploying agentic systems that reason over live infrastructure
Proficiency in prototyping and iterating quickly based on customer feedback
Experience with graph-native retrieval, MCP tooling, and structured context
Knowledge of graph models, knowledge graphs, or observability tools
Ability to own the reliability and scale of AI systems in a production environment