Cybersecurity AI Architect

Generac; Ramban district; On-site; INR 2,500,000 - 4,500,000; Full time

Job summary

Generac is seeking an AI Security Architect to define secure architectures for LLM, RAG, and AI-enabled systems across cloud and enterprise environments. Lead threat modeling and controls for prompt injection, data leakage, and model abuse while embedding security into engineering workflows and production deployments.

Collaborate with cross-functional teams to establish standards for identity, data classification, logging, and third-party AI services.

Qualifications

• Bachelor’s degree in cybersecurity, CS, IS, or related field.
• 7+ years in cybersecurity or security architecture.
• Hands-on with cloud security and AI platforms.

Responsibilities

• Defines secure reference architectures for AI systems across cloud and on-prem.
• Leads AI threat modeling and design controls for prompts, data leakage, and abuse.
• Establishes architecture standards for identity, secrets, data, network, logging, and model access.
• Designs guardrails for input filtering, grounding controls, policy enforcement, and monitoring.
• Partners with engineering to embed security into AI platforms, CI/CD pipelines, and production deployments.
• Evaluates AI security tooling, posture management, red teaming, model testing, and policy enforcement.
• Creates implementation guidance and design reviews for secure AI features at scale.
• Supports incident readiness with telemetry, detections, escalation points, and response for AI events.
• Influences governance by aligning architecture with risk, privacy, and acceptable-use expectations.

Skills

AI security

Threat modeling

Security architecture

Cloud security

IAM

Stakeholder comms

Security standards

Education

Bachelor’s degree in Cybersecurity, CS, IS, or related

Master’s degree in related field

Tools

AWS Bedrock

Anthropic

Azure OpenAI

Google Vertex AI

Job description

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

Minimum Job Requirements

Education

• Bachelor’s degree in Cybersecurity, Computer Science, Information Security, Software Engineering, Computer Engineering, or a related technical field

Certification / License

• Cloud security, security architecture, or AI/ML related certifications are helpful but not required

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.

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

Work 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

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