Forward Deployed AI Security Lead

Forward Deployed AI Security Lead

Location:

Plano, Texas

Toyota Financial Services (TFS) Technology team is looking for a highly motivated person to fill a role as a Forward Deployed AI Security Lead within the Security Intelligence Engineering organization. You will own the intelligence platform end‑to‑end: from API integrations with enterprise security tools, to a cross‑source correlation engine, to an agentic AI layer that autonomously triages security findings at scale, to dashboards that deliver actionable intelligence to multiple security teams.

You will operate at the intersection of security operations, AI/ML engineering, and cloud platform development, embedding directly with security team leads to understand their workflows and building AI systems that transform them.

• Embed directly with security team leads across multiple functions to deeply understand their workflows, tools, and pain points
• Lead discovery sessions to identify high‑value automation opportunities — translating security operations problems into AI‑solvable technical specifications
• Own the structured intake process: prioritize requests by cross‑team impact and risk reduction value, communicate capacity and timelines transparently
• Design and build multi‑agent architectures using managed AI services — autonomous triage agents, cross‑source correlation agents, and team‑specific specialist agents
• Implement RAG systems over a centralized security data lake for natural language threat hunting and investigation
• Build prompt engineering patterns, evaluation frameworks, and feedback loops that continuously improve agent accuracy
• Design a model routing layer that directs each task to the optimal model based on complexity, latency, and cost
• Implement centralized token usage monitoring and cost controls for leadership visibility
• Own agent observability: monitoring for drift, hallucination detection, accuracy degradation, and failure mode identification
• Architect human‑in‑the‑loop controls and guardrails ensuring agents operate safely within defined boundaries
• Design and build API connectors to enterprise security tools (EDR/XDR, cloud security, API security, identity, vulnerability management)
• Architect the cross‑source correlation engine that links findings across endpoint, cloud, identity, and network data
• Define and evolve the data lake schema and ingestion pipelines for security telemetry
• Build and maintain dashboards serving multiple security teams with team‑specific views
• Set engineering standards, code review practices, and architectural patterns as the team grows
• Serve as the trusted technical advisor to security leadership — translating complex AI/ML capabilities into clear, actionable security outcomes

• 5+ years building production systems, with strong Python and Type Script fluency
• 1+ years hands‑on experience with LLMs in production or near‑production contexts — prompt engineering, RAG architectures, agentic workflows, or fine‑tuning
• Hands‑on experience with security tool APIs — particularly EDR/XDR platforms
• Strong AWS foundation: S3, Lambda, RDS, IAM, VPC, and familiarity with managed LLM services (e.g., Amazon Bedrock)
• Understanding of security operations workflows — alert triage, investigation chains, incident response, threat intelligence correlation
• Demonstrated ability to work directly with non‑engineering stakeholders: translating business/operational problems into technical solutions, managing expectations, and delivering outcomes
• Experience building full‑stack applications (API layer + frontend) that serve multiple user groups
• Strong communication and interpersonal skills with the ability to influence cross‑functional teams without direct authority

• Experience with multi‑agent orchestration frameworks
• Background in a forward‑deployed, solutions engineering, or customer‑embedded technical role — or early‑stage startup experience
• Experience with cloud security posture management platforms
• MITRE ATT&CK framework knowledge and practical application to detection engineering
• Experience building evaluation pipelines for AI systems — automated metrics, human evaluation protocols, A/B…