Sr. Security Engineer (DLP) (Hyderabad)

We are seeking a Senior Information Security Engineer to help transform the Intellectual Property (IP) protection program through advanced, AI-driven data loss prevention (DLP) and data labeling capabilities. This role goes beyond traditional rule-based DLPfocusing on contextual understanding of data, users, and behavior, large-scale discovery of sensitive IP, and adaptive, automated controls powered by machine learning and generative AI technologies Key responsibilities DLP Architecture & Operations - Design and deploy DLP capabilities that understand data sensitivity, business context, user intent, and behavioral risk, rather than relying solely on patterns or keywords. - Build detection rules for source code, hardware design files, algorithms, product roadmaps, and other IP artifacts (e.g., complex regex, fingerprints, EDM/IDM, ML-based classifiers). - Tune and optimize policies to reduce false positives/negatives; implement tiered response workflows and auto-remediation actions. - Establish monitoring for egress vectors (USB/removable media, print, email, SaaS, personal webmail, messaging, generative AI tools, cloud sync). - Develop detections for anomalous IP access/exfil patterns (e.g., code repo mirroring, bulk downloads, atypical off-hours activity). - Identify early indicators of IP misuse or exfiltration through behavioral analytics rather than reactive alerting. - Define guardrails for the secure use of generative AI tools, ensuring proprietary data and IP are protected from unintended disclosure - Author and maintain IP protection standards, DLP/runbooks, and exception processes. - Define and track KPIs/KRIs (e.g., DLP alert quality, mean time to triage/close, exfil attempts prevented, classification coverage). Data Classification & Labeling - Implement scalable AI-assisted data discovery across endpoints, cloud services, SaaS platforms, and code repositories to identify previously unknown or unclassified IP. - Implement and scale enterprise data classification and labeling for IP-heavy content. - Drive adoption via policy-based auto-labeling, built-in nudges, and sensitivity label inheritance through workflows and repositories. - Implement conditional access, DRM, and rights management for sensitive content shared internally and externally. Qualifications and Experience - Robust understanding of AI concepts, machine learning pipelines, and automation tools. - Hands-on experience or coursework in Copilot Studio, UiPath, and SharePoint. - Knowledge with cloud AI platforms: Azure AI Foundry, AWS Bedrock, etc. - Experience in leveraging, creating, and driving AI in DLP solutions - Minimum 4 years of experience in information security with hands-on DLP and/or data classification/labeling at scale. - Proven experience designing and tuning DLP policies for endpoints, email, web, and SaaS - Practical knowledge of IP data types (source code, firmware, design files, algorithms, roadmaps) and how they move across an enterprise. - Strong operational understanding of using custom keywords and dictionaries - Strong knowledge of networking and operating systems - Knowledge of cloud service providers, including Azure, AWS, and GCP - Hands-on expertise SIEM/SOAR platforms. - Scripting/automation proficiency (PowerShell, Python, or Splunk SPL). - Excellent written and verbal communication skills Education: - B.Tech degree in Computer Science, Computer Engineering, other technical disciplines, or equivalent work experience. - Candidates with a masters degree in technology or science and relevant professional certifications are preferred. We are seeking a Senior Information Security Engineer to help transform the Intellectual Property (IP) protection program through advanced, AI-driven data loss prevention (DLP) and data labeling capabilities. This role goes beyond traditional rule-based DLPfocusing on contextual understanding of data, users, and behavior, large-scale discovery of sensitive IP, and adaptive, automated controls powered by machine learning and generative AI technologies Key responsibilities DLP Architecture & Operations - Design and deploy DLP capabilities that understand data sensitivity, business context, user intent, and behavioral risk, rather than relying solely on patterns or keywords. - Build detection rules for source code, hardware design files, algorithms, product roadmaps, and other IP artifacts (e.g., complex regex, fingerprints, EDM/IDM, ML-based classifiers). - Tune and optimize policies to reduce false positives/negatives; implement tiered response workflows and auto-remediation actions. - Establish monitoring for egress vectors (USB/removable media, print, email, SaaS, personal webmail, messaging, generative AI tools, cloud sync). - Develop detections for anomalous IP access/exfil patterns (e.g., code repo mirroring, bulk downloads, atypical off-hours activity). - Identify early indicators of IP misuse or exfiltration through behavioral analytics rather than reactive a