Cybersecurity AI Architect

Knowledge / Skills / Abilities Ability to balance secure by design principles with speed of delivery, and to convert emerging AI risks into practical standards, reusable patterns, and engineering guidance

About Generac

• We are Generac, a leading energy technology company committed to powering a smarter world.
• Over the 60 plus years of Generac’s history, we’ve been dedicated to energy innovation.
• From creating the home standby generator market category, to our current evolution into an energy technology solutions company, we continue to push new boundaries.

Responsibilities

• Major Responsibilities • Defines secure reference architectures for LLM, RAG, agentic, and other AI enabled systems across cloud and enterprise environments • Leads AI threat modeling and identifies design controls for prompt injection, insecure output handling, excessive agent permissions, model abuse, data leakage, and supply chain risk • Establishes architecture standards for identity, secrets management, data classification, network boundaries, logging, model access, and third party AI service consumption. • Designs guardrails and security patterns for input filtering, grounding controls, policy enforcement, human in the loop checkpoints, and runtime monitoring • Partners with engineering teams to embed security requirements into AI platforms, developer workflows, CI/CD pipelines, and production deployment patterns. • Drives evaluation of AI security tooling, including posture management, red teaming, model and prompt testing, observability, and policy enforcement capabilities • Creates implementation guidance, reference patterns, and design reviews that help teams deliver secure AI features consistently at scale • Supports incident readiness by defining telemetry, detections, escalation points, and response considerations for AI specific security events • Influences enterprise AI governance by connecting architecture decisions to risk, compliance, privacy, and acceptable use expectations

Requirements

• Job Requirements Education Bachelor’s degree in Cybersecurity, Computer Science, Information Security, Software Engineering, Computer Engineering, or a related technical field
• Certification / License Work Experience • 7 years of experience in cybersecurity, software security, cloud security, or security architecture roles • 2 years of direct experience designing or securing AI, ML, LLM, or data intensive platforms in production environments • Hands on experience with cloud native architecture patterns in AWS, Azure, or GCP, including IAM, logging, networking, encryption, and secrets management • Experience performing threat modeling, architecture review, and security design for modern applications, APIs, and distributed systems
• Knowledge / Skills / Abilities Strong understanding of AI system components, including models, prompts, retrieval layers, agents, plugins, orchestration frameworks, and data pipelines.
• Working knowledge of AI security risks such as prompt injection, insecure tool use, excessive autonomy, training data exposure, sensitive data leakage, and model supply chain concerns.
• Strong grasp of core security architecture domains, including identity, cryptography, application security, cloud security, logging, monitoring, and incident response.
• Clear communicator who can work across engineering, product, privacy, legal, and executive stakeholders Ability to translate security risk into practical technical requirements and influence engineers, architects, and platform owners.
• Experience • Experience securing AI platforms built on services such as AWS Bedrock, Anthropic, Azure OpenAI, Microsoft Azure AI, Google Vertex AI, or equivalent • Experience with AI security testing, red teaming, prompt attack evaluation, or model and agent assessment techniques • Familiarity with orchestration and agent frameworks • Experience implementing policy, observability, and runtime control layers around AI systems and external tools • Exposure to governance frameworks such as NIST AI RMF, OWASP Top 10 for LLM Applications, MITRE ATLAS, or similar guidance

Preferred

• Job Requirements Education Bachelor’s or Master’s degree in Cybersecurity, Computer Science, Software Engineering, Data Science, Machine Learning, or a related technical discipline.
• Certification / License Cloud security, security architecture, or AI/ML related certifications are helpful but not required