Senior AI Engineer

Radiant Security is building the most advanced AI SOC platform, featuring unbounded alert triage, investigation, and response for security teams at scale. Our platform ingests alerts from across an organization's entire security stack (SIEM, EDR, identity, cloud) and uses AI to triage, investigate, and surface what actually matters. We're replacing alert fatigue with clear signal, so analysts can focus on real threats. Our product touches the daily workflows of security teams, and decisions we make have a direct impact on how quickly threats get resolved.

The Role: In this role, you'll build the agentic systems that turn overwhelming alert volume into clear, confident decisions, pipelines where AI agents collaborate, reason, and escalate the way the best analysts do, but at machine speed and scale. This isn't prompt experimentation in a notebook. You'll own the full lifecycle of production pipelines: the retrieval systems that surface the right context, the routing logic that sends data where it needs to go, the DAG that encodes the decision structure of a real security problem, and the agents themselves that reason over it all.

What you'll do:

• 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.
• Context Retrieval & Data Routing: Build the retrieval and enrichment systems that feed agents the context they need: structured lookups, vector search, tool calls, API integrations, or database queries.
• Agent Development & Prompt Engineering: Design and build individual agents with well-scoped, production-ready prompts tailored to specific cybersecurity tasks (alert classification, entity extraction, severity scoring, false positive filtering). Apply systematic prompt optimization techniques.
• LLM Lifecycle Management: Evaluate new or alternative LLMs using structured methodologies and project-specific metrics.
• Production Operations & Evaluation: Monitor pipeline performance end-to-end in production, latency, accuracy, cost, failure modes, and per-stage quality.

Required Qualifications:

• Strong programming skills in Python; 5 years of experience building and deploying production services end-to-end.
• Hands-on experience with LLM APIs (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.

Preferred Qualifications:

• Background in cybersecurity, SOC operations, or threat intelligence.
• Experience with evaluation frameworks (RAGAS, LangSmith, custom harnesses).
• Exposure to agentic frameworks (LangGraph, CrewAI, AutoGen, or custom implementations).

This role is based in the United States and requires authorization to work in the U.S.