Director, Security Engineering - AI

myhrabc; Pune District; On-site; INR 700,000 - 1,200,000; Full time

Job summary

Cencora seeks a Director of AI Security to build and lead an India-based security engineering and enablement function protecting enterprise AI adoption across generative AI, copilots, agents, and ML platforms. The role reports to the U.S.

Senior Director, Data & AI Security, with a dotted line to the India Senior Director, Endpoint & Infrastructure Security. The position is strategic and technical, focusing on securing AI while enabling innovation, managing data leakage, prompt injection, IP

Qualifications

• 12+ years in cybersecurity.
• Experience leading AI security programs.
• Strong security architecture and governance experience.

Responsibilities

• Translate enterprise AI security strategy into India-based delivery plans and roadmaps.
• Lead design and implementation of security controls for AI platforms, models, and integrations.
• Define and operate controls for prompt injection, data leakage, and model risk in collaboration with risk, privacy, and legal teams.
• Partner with global security teams to ensure AI telemetry, monitoring, and incident response.
• Build and lead an India-based AI security team spanning architecture, engineering, and governance enablement.

Job description

Our team members are at the heart of everything we do. At Cencora, we are united in our responsibility to create healthier futures, and every person here is essential to us being able to deliver on that purpose. If you want to make a difference at the center of health, come join our innovative company and help us improve the lives of people and animals everywhere.

Job Details

Role Summary

The Director, AI Security will build and lead an India-based AI security engineering and enablement function responsible for protecting enterprise use of artificial intelligence: generative AI, copilots, agents, large language models, machine learning platforms, AI-enabled SaaS, and AI-integrated business workflows. Reporting to the U.S.-based Senior Director, Data & AI Security, with a dotted line to the India-based Senior Director, Endpoint & Infrastructure Security, this role translates global AI security strategy into scalable engineering, control, and governance outcomes. It is both strategic and technical, and focused on securing AI adoption without blocking innovation while addressing data leakage, prompt injection, model misuse, insecure integrations, shadow AI, agentic workflow risk, and intellectual property exposure. The role establishes India as a strategic global center of excellence for AI security engineering and operations, not only a delivery location.

Key Responsibilities

AI Security Strategy and Execution

Translate enterprise Data & AI Security strategy into India-based delivery plans, engineering roadmaps, and measurable objectives. Lead design and execution of security controls across internally developed models, third-party AI services, SaaS AI features, copilots, retrieval-augmented generation, agentic workflows, and AI-enabled automation. Establish practical AI security patterns that enable innovation while protecting sensitive data, regulated information, credentials, and IP.

AI Security Architecture and Engineering

Lead AI security architecture across enterprise AI platforms, cloud AI services, model integrations, data pipelines, and AI-enabled applications. Create and maintain secure design patterns for generative AI platforms, LLM and model API integrations, RAG systems, vector databases and embeddings, AI agents and tool invocation, prompt and response handling, and human-in-the-loop controls. Ensure designs address confidentiality, integrity, availability, identity, data protection, privacy, auditability, resilience, and abuse prevention.

AI Risk Management and Control Design

Define and operationalize controls for prompt injection (direct and indirect), sensitive data leakage, model manipulation and abuse, insecure plugin/tool/agent integrations, unauthorized access through RAG or connectors, excessive agency and unsafe automation, shadow AI, insecure model supply chain, and IP exposure. Partner with risk, legal, privacy, and compliance to ensure AI controls are practical, enforceable, and measurable. Partner with Data Security and Privacy on classification, minimization, residency, DLP, encryption and key management, entitlement review, retention, and training and RAG corpus governance - ensuring AI does not create uncontrolled copies, embeddings, or derived data stores outside enterprise governance.

Cross-Domain Control Integration

Work with the India-based Senior Director, Endpoint & Infrastructure Security to embed AI security requirements into endpoint, browser, infrastructure, collaboration, developer, and platform controls. Drive integration across secure access to AI tools from managed and unmanaged endpoints, endpoint DLP, device posture and conditional access, developer workstation protections for AI-assisted coding, secrets protection, secure hosting of AI workloads, and AI telemetry.

Secure AI Adoption, Assurance, and Operations

Build practical enablement: AI security intake, risk tiering, assessment templates, control requirements, approved-tool guardrails, shadow AI discovery, production readiness checklists, and exception models. Lead or enable AI security testing for prompt injection, RAG data leakage, authorization bypass, connector misuse, unsafe agent actions, excessive permissions, adversarial input, and AI-generated code risk - in partnership with application security, red team, and model risk. Partner with cyber defense and the SOC to define AI telemetry, monitoring, and incident response playbooks covering AI tool usage, high-risk prompt and response patterns, sensitive data movement, connector and agent activity, and shadow AI indicators.

Team Leadership and India Capability Building

Build and lead an India-based AI security team spanning architecture, engineering, assurance, governance enablement, and technical program management. Develop a leadership bench and technical career path across AI security architecture, cloud and platform security, application and API security, AI security testing, and automation.

Required Experience

12+ years in cybers