Data Security Engineer at S&P Global

About the Role: S&P Global's IP Security team is seeking a Data Security Engineer to join their ranks in Gurugram, India. This role is crucial for safeguarding the company's intellectual property, including source code, models, datasets, and architectural designs. The team establishes the standards and controls to prevent IP leakage and misuse, enabling product teams to innovate securely and compliantly.

Key Responsibilities:

• Develop and implement AI/ML security strategies, policies, and standards to protect organizational assets and ensure secure AI/ML system operations.
• Build security control frameworks and reference architectures for Generative AI applications.
• Assist LoB/Dev teams in identifying security requirements for GenAI application development.
• Conduct threat modeling exercises to identify security risks and vulnerabilities in AI systems, integrating security into the design and development lifecycle.
• Provide thought leadership to mature GenAI security governance within the existing cybersecurity risk appetite framework.
• Perform security assessments on AI applications and systems, developing testing methodologies to evaluate the security posture of AI models and frameworks.
• Develop configuration hardening guidelines for Cloud Services, including native Generative AI/ML services on AWS, Azure, and GCP (e.g., SageMaker, Bedrock, Cognitive Services, Vertex AI).
• Stay updated on AI security regulations and standards, collaborating with legal and compliance teams to ensure alignment.

Core Skills Required:

• Strong programming experience in Python or equivalent languages.
• Solid understanding of LLM/GenAI fundamentals: prompting, embeddings, vector search, RAG, and basic agentic patterns.
• Experience running production systems or data pipelines on AWS, Azure, or GCP, utilizing containers, serverless, and managed services.
• Hands-on familiarity with observability tools (e.g., OpenTelemetry, Prometheus, Grafana, ELK) for logs, metrics, and traces.
• Proficiency in handling structured and unstructured data, with strong SQL and experience in frameworks like Pandas, Spark, or dbt.
• Ability to make reasoned trade-offs regarding reliability, performance, and cost.
• Strong collaboration and communication skills, with the ability to explain complex concepts to diverse teams.

Qualifications:

• 15 years of experience in cybersecurity, software engineering, data engineering, ML engineering, or data science.
• Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or equivalent practical experience.
• Experience with CI/CD, code reviews, and modern engineering best practices.

Nice To Have:

• Exposure to agentic AI frameworks (e.g., LangChain, LangGraph, OpenAI Agents).
• Experience with LLM observability, evaluation frameworks, or prior work on production LLM/agent systems.

What We're Looking For:

• Engineers who build for scale, lead with observability, ship safely, make thoughtful trade-offs, own the end-to-end stack, learn through experimentation, communicate with impact, and stay ahead of emerging technologies.