Senior Full-Stack Engineer, Autonomous Defense
New
H
Horizon3Cybersecurity
US, RemoteFull-TimeSenior
SalaryBase salary range: $195,000- $235,000 annually. Additional compensation: All full-time roles are eligible for an equity package in the form of stock options.
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Job Details
- Experience
- 7+ yrs professional software engineering experience
- Required Skills
- DockerGraphQLPythonSQLKubernetesTypeScriptC++GoReactScala
Requirements
- Bachelor’s degree in Computer Science, Computer Engineering, or a related field.
- 7+ years of professional software engineering experience using modern object-oriented or functional languages.
- Experience delivering backend APIs, especially GraphQL, and consuming them from a modern web stack.
- Production experience with React, TypeScript, and modern CSS layout.
- Experience building applications on cloud platforms such as AWS, Azure, or GCP.
- Experience with container technologies such as Docker and Kubernetes.
- Expert proficiency in SQL.
- Experience designing and operating production distributed systems, including asynchronous workflows, queues, retries, idempotency, and partial failure.
- Experience shipping and operating production services, including on-call ownership.
- Up to 5% travel may be required.
Responsibilities
- Build and own durable, resumable agent execution workflows with checkpointing, idempotent steps, cancellation, and timeouts.
- Design the agent tool registry with versioning, schema validation, per-tenant enablement, and server-side authorization.
- Build a connector framework for third-party security control planes.
- Implement simulation, blast-radius classification, approval gates, staged rollout, rollback, and immutable per-tenant audit trails.
- Build operator-facing interfaces in React and TypeScript.
- Develop client-side data and streaming capabilities over WebSockets for long-running, incrementally updating state.
- Extend tenant isolation for agent write actions, including execution boundaries, egress control, quotas, and cross-tenant leakage prevention.
- Develop ETL and GraphQL product features and pipelines for agent context, run history, remediation state, and research datasets.
- Instrument agent runs with distributed tracing, per-tenant cost and token accounting, and debugging tools.
- Partner with AI researchers, attack engineers, and product to bring capabilities from prototype to production.
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