Radiant Security
Senior AI Engineer
United States · Senior
Sponsorship not specifiedDetected 78 days ago
PythonLLMsAgentic AILangGraphA/B TestingCybersecuritySIEMSOC OperationsManual TestingExperimental DesignCommunication
About the role
- Cybersecurity generates more signal than any human team can process.
- The AI Engineer's job is to change that.
Responsibilities
- DAG Design & Pipeline Orchestration
- Design and implement the DAG-based pipeline architecture. Decompose complex cybersecurity workflows into well-scoped pipeline stages and define data contracts between them.
- Build the retrieval and enrichment systems that feed agents the context they need: structured lookups, vector search, tool calls, API integrations, or database queries.
- Design routing logic that directs incoming data to the appropriate pipeline entry point or agent branch.
- Design and build individual agents with well-scoped, production-ready prompts tailored to specific cybersecurity tasks (e.g., alert classification, entity extraction, severity scoring, false positive filtering).
- Monitor pipeline performance end-to-end in production - latency, accuracy, cost, failure modes, and per-stage quality - and drive continuous improvement across all layers.
- Build and curate labeled datasets from production telemetry for evaluation, regression testing, and fine-tuning purposes.
Requirements
- 5 years of experience building and deploying production services end-to-end.
- Hands-on experience with LLM APIs (e.g., OpenAI, Anthropic, Gemini) and prompt engineering techniques.
- Experience designing and implementing DAG-based workflows or pipeline orchestration systems.
- Familiarity with data retrieval patterns: vector search, structured queries, API integrations, and context assembly for LLM consumption.
- Ability to work with unstructured or semi-structured data in a security or operational context.
Nice to have
- Background in cybersecurity, SOC operations, or threat intelligence.
- Experience with evaluation frameworks (e.g., RAGAS, LangSmith, custom harnesses).
- Familiarity with fine-tuning, RLHF, or model distillation workflows.
- Exposure to agentic frameworks (e.g., LangGraph, CrewAI, AutoGen, or custom implementations).
- We're a startup and we make decisions quickly.
Skills
- About Radiant Security
- Join us and boost your career with hands-on AI experience.
- This isn't prompt experimentation in a notebook.
Company info
- Things we're looking for
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This listing is sourced directly from Radiant Security's careers page and normalized into a canonical job model.