AI ML Security Architect

Tata Consultancy Services (TCS) is an equal opportunity employer, and embraces diversity in race, nationality, ethnicity, gender, age, physical ability, neurodiversity, and sexual orientation, to create a workforce that reflects the societies we operate in. Our continued commitment to Culture and Diversity is reflected in our people stories across our workforce and implemented through equitable workplace policies and processes.

Security Architect to assure enterprise security architecture with a focus on the review and authorship of Architecture Decision Records (ADRs) and Security Architecture Review Board (SARB) submissions. The role blends deep technical acumen with emerging expertise in Generative AI (GenAI) and Agentic systems, ensuring secure design, governance, and responsible adoption of intelligent automation within the enterprise.

• Lead architecture review & advisory for solution and domain architectures, ADRs, and AI‑enabled platforms.
• Assess GenAI and agentic solution designs for model security, data protection, prompt integrity, provenance, and safe orchestration of agents.
• Evaluate proposals for alignment with enterprise standards, regulatory expectations, and risk tolerance.
• Produce actionable review comments with traceable recommendations, covering both traditional and AI‑driven architectures.
• Author and maintain ADRs, patterns, and reference architectures—including those covering GenAI system integration, LLM usage, and multi‑agent frameworks.
• Ensure architectural documentation expresses problem space, options, controls, and trade‑offs clearly and defensibly.
• Promote structured architectural reasoning supported by human and GenAI‑assisted analysis workflows.
• Define and assess controls for GenAI systems, covering model access, data boundaries, and prompt injection defenses.
• Implement guardrails for AI agents performing autonomous actions or multi‑step reasoning: secure orchestration, isolation, and human oversight.
• Evaluate security of agent frameworks, LLM pipelines, and model‑hosting platforms (e.g., Vertex AI, Azure OpenAI).
• Contribute to enterprise policy for responsible AI use and GenAI‑assisted development.
• Provide domain expertise in application, cloud, and data security—augmented by AI security design considerations.
• Support teams in safely embedding GenAI copilots, RAG systems, and autonomous agents within business processes.
• Lead threat modeling for composite systems where GenAI interacts with APIs, data stores, and user environments.
• Use and refine GenAI tools for document review, security design assistance, and ADR quality assurance.
• Develop reusable prompts, review heuristics, and decision frameworks that enhance SARB throughput and consistency.
• Mentor peers in human‑AI collaborative authoring, emphasizing accountability and verification of AI output.

• Broad experience across cloud, data, application, and API security domains.
• Proficiency with tools for architectural diagramming, review automation, and GenAI‑assisted design (e.g., Lang Chain, OpenAI GPT, Guardrails AI).
• Strong authorship and analytical writing—clear articulation of decisions and consequences.
• Knowledge of enterprise security architecture frameworks (e.g., SABSA, TOGAF, NIST CSF).
• Experience with GenAI system architecture, LLM lifecycle, and model governance.
• Familiarity with security patterns for threat modeling of LLMs, data leakage prevention, and agent control.
• Ability to author Architecture Decision Records (ADRs) and maintain reference architectures.

Toronto, ON