GDS Cyber-DPP-Senior-AI Data Protection Engineering
Ernst and Young2 months ago
Pune, IndiaStaff+
Responsibilities
- Lead engineering design and implementation of AI-enabled data protection solutions covering discovery/classification, protection controls, PKI/KMS integrations, and rights management.
- Build automation for deployment, policy tuning, control validation, reporting, and operational workflows using scripting, APIs, and engineering tooling.
- Design and deploy hybrid and agentic patterns integrating data protection platforms, AI tools, and enterprise data and workflow systems.
- Own technical workstreams in client engagements, including design decisions, engineering quality, integrations, troubleshooting, and stabilization planning.
- Create reusable prompts, engineering patterns, code libraries, configuration baselines, implementation templates, testing artifacts, and other delivery accelerators.
- Mentor junior engineers through code reviews, knowledge transfer, technical coaching, and contributions to engineering standards.
- Collaborate with data protection, AI engineering, privacy, and cloud teams to deliver scalable and compliant solutions.
Requirements
- 5–8 years of experience in data protection engineering, cybersecurity engineering, privacy engineering, cloud security engineering, or adjacent domains.
- Strong hands-on experience with data protection, data discovery/classification, PKI and KMS, and information rights management.
- Working knowledge of ML, deep learning, NLP, RAG, AI-assisted prioritization, and model risk scoring for production-oriented delivery.
- Experience with one or more of Microsoft Purview, Cyera, Varonis, Sentra, CrowdStrike Falcon DSPM, or Wiz DSPM.
- Strong Python scripting and integration skills, including experience with APIs, cloud services, and engineering toolchains.
- Ability to independently lead technical workstreams in ambiguous, client-facing delivery environments.
- Experience with automated policy deployment, classification engineering, data mapping, or AI-enabled triage/orchestration patterns is preferred.
- Familiarity with privacy and cross-border data transfer considerations in AI use cases is preferred.
- Experience contributing to internal assets, managed services, or engineering standards in a professional services or product engineering environment is preferred.
Benefits
- Global, cross-functional work environment across advisory, architecture, engineering, and delivery.
- Exposure to strategic client programs and market-shaping offerings.
- Opportunity to build reusable assets, accelerators, and modernization patterns within a globally connected cybersecurity practice.
Tech Stack
Categories
Solutions Engineering
About Ernst and Young
Ernst & Young (EY) provides audit/assurance, tax, consulting, strategy and transactions services to enterprises, financial institutions, and public‑sector clients. Structured as a global network of partner‑owned member firms, it sells professional services on a fee basis, including a dedicated Financial Services Organization for banking, insurance, and capital markets. Headquartered in London, EY was formed in 1989 from the merger of Ernst & Whinney and Arthur Young, and operates in 150+ countries.