Lead AI Security Engineer-IDP

Societe Generale Global Solution Centre; Bengaluru; On-site; INR 4,000,000 - 6,500,000; Full time

Job summary

Societe Generale Global Solution Centre seeks a Lead AI Security Engineer to secure enterprise AI platforms, GenAI apps, LLM integrations, and AI-enabled services across their lifecycle. The role emphasizes hands-on security execution, threat modelling, and practical risk mitigation.

You will collaborate with engineering, platform, cloud, data, and architecture teams to embed AI security requirements into design, build, deploy, and operate cycles, ensuring scalable, enterprise-grade controls.

Qualifications

• 10+ years in cybersecurity or security engineering with focus on AI security.
• Hands-on experience securing AI/ML/GenAI platforms and pipelines.
• Knowledge of risk assessment, threat modelling, and security controls.
• Familiarity with OWASP LLM Top 10, MITRE ATLAS, and NIST AI RMF.

Responsibilities

• Lead AI security engineering, threat modelling, and control design.
• Design and validate security controls for AI platforms and workflows.
• Partner with engineering, cloud, data, and security teams to embed requirements.
• Perform adversarial testing, attack surface reviews, and risk mitigation.
• Define monitoring, logging, and incident readiness for AI systems.

Skills

AI security

Threat modelling

Security architecture

Cloud security

Adversarial testing

Governance

Stakeholder management

Frameworks knowledge

Tools

Azure OpenAI

Databricks

Snowflake

Microsoft Purview

Job description

Lead AI Security Engineer

About the Role

We are hiring a Lead AI Security Engineer to secure enterprise AI platforms, GenAI applications, LLM-based solutions, AI agents, and AI-enabled services across their full lifecycle. The role will focus primarily on AI security engineering, threat modelling, architecture assurance, secure AI control design, adversarial testing, and practical risk mitigation. Governance, standards, and risk reporting are part of the role, but they are secondary to hands‑on AI security execution and the ability to translate AI‑specific threats into secure, scalable, and enterprise‑ready technical controls.

Key Responsibilities

• AI Security Engineering & Architecture
• Design and validate security controls for AI platforms, GenAI applications, LLM integrations, RAG pipelines, AI agents, model endpoints, and AI-enabled workflows.
• Partner with engineering, platform, cloud, data, application security, and architecture teams to embed AI security requirements into design, build, deployment, and operations.
• AI Threat Modelling, Testing & Risk Mitigation
• Identify and assess AI‑specific threats including prompt injection, jailbreaks, insecure tool use, data leakage, model extraction, poisoning, RAG abuse, agent misuse, and AI supply chain exposure.
• Conduct AI threat modelling, adversarial testing, attack surface reviews, control gap analysis, residual risk documentation, and mitigation planning across platforms such as DATALABS, AI Foundry, Azure Cognitive Services, Databricks, and Snowflake.
• Secure AI Controls, Monitoring & Compliance Support
• Define and review controls for model access, prompt and response handling, sensitive data protection, identity and access, secure APIs, logging, monitoring, abuse detection, and incident readiness for AI systems.
• Use frameworks such as OWASP Top 10 for LLM Applications, MITRE ATLAS, NIST AI RMF, Responsible AI, and EU AI Act expectations as supporting references for control alignment and audit readiness.
• AI Security Governance, Enablement & Operational Excellence
• Support AI cybersecurity standards, secure design patterns, assessment checklists, governance inputs, and awareness material while keeping the primary focus on practical security implementation.
• Improve AI security metrics, risk visibility, control automation, and reusable security guidance in partnership with platform, cyber, architecture, and automation teams.

Required Skills

10+ years in cybersecurity, security architecture, application security, cloud security, AI/ML security, or enterprise security engineering.

AI Security

Strong hands‑on experience securing AI, ML, GenAI, LLM applications, RAG pipelines, AI agents, model APIs, or enterprise AI platforms.

AI Threat Knowledge

Deep understanding of prompt injection, jailbreaks, insecure plugins/tools, model poisoning, data leakage, model exfiltration, RAG security, agent security, AI supply chain risk, AI red teaming, and misuse scenarios.

Frameworks & Standards

Working knowledge of OWASP LLM Top 10, MITRE ATLAS, NIST AI RMF, Responsible AI, and AI regulatory expectations to support control alignment and governance activities.

Security Assurance

Experience designing, validating, and operationalizing AI security controls, including secure architecture reviews, threat modelling, adversarial testing, remediation tracking, and risk acceptance support.

Enterprise Security

Strong knowledge of cloud security, application security, API security, data protection, IAM, logging, monitoring, security operations, and enterprise risk management as applied to AI systems.

Stakeholder Management

Ability to work with engineering and senior stakeholders, explain AI security risks clearly, and convert them into practical technical controls and mitigation actions.

Preferred Experience

• Experience with AI security engineering, AI red teaming, adversarial testing, model robustness evaluation, secure RAG design, agent security, or AI platform security in regulated environments.
• Experience with enterprise AI platforms such as Azure OpenAI, Microsoft AI Foundry, Azure AI Services, Databricks, Snowflake, Microsoft Purview, or Microsoft security technologies.
• Exposure to Responsible AI, model risk management, AI governance programs, Python scripting, automation, or relevant security certifications such as CISSP, CISA, CRISC, GIAC, CCSP, or ISO 27001.

Candidate Profile

• Hands‑on AI security expert who can lead secure architecture reviews, threat modelling, control design, testing, and risk mitigation for enterprise AI systems.
• Comfortable working across cybersecurity, platform engineering, cloud, data, AI, architecture, compliance, risk, automation, and business teams in a complex global environment.
• Demonstrates ownership, clear communication, and the ability to improve AI security maturity while keeping governance practical, lightweight, and aligned to delivery needs.

Why join us

We are committed to creating a diverse environment and are proud to be an equal opportunity employer. All qualified applicants receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.

Business insight

At Société Générale, we are convinced that people are drivers of change, and that the world of tomorrow will be shaped by all their initiatives, from the smallest to the most ambitious. Whether you’re joining us for a period of months, years or your entire career, together we can have a positive impact on the future. Creating, daring, innovating, and taking action are part of our DNA. If you too want to be directly involved, grow in a stimulating and caring environment, feel useful on a daily basis and develop or strengthen your expertise, you will feel right at home with us!

Still hesitating?

You should know that our employees can dedicate several days per year to solidarity actions during their working hours, including sponsoring people struggling with their orientation or professional integration, participating in the financial education of young apprentices, and sharing their skills with charities. There are many ways to get involved. We are committed to support accelerating our Group’s ESG strategy by implementing ESG principles in all our activities and policies. They are translated in our business activity (ESG assessment, reporting, project management or IT activities), our work environment and in our responsible practices for environment protection.