About this role
EXL (NASDAQ: EXLS) is a leading data analytics and digital operations and solutions company. We partner with clients using a data and AI-led approach to reinvent business models, drive better business outcomes and unlock growth with speed. EXL harnesses the power of data, analytics, AI, and deep industry knowledge to transform operations for the world’s leading corporations in industries including insurance, healthcare, banking and financial services, media and retail, among others. EXL was founded in 1999 with the core values of innovation, collaboration, excellence, integrity and respect. We are headquartered in New York and have more than 54,000 employees spanning six continents. For more information, visit www.exlservice.com.
EXL never requires or asks for fees/payments or credit card or bank details during any phase of the recruitment or hiring process and has not authorized any agencies or partners to collect any fee or payment from prospective candidates. EXL will only extend a job offer after a candidate has gone through a formal interview process with members of EXL’s Human Resources team, as well as our hiring managers.
• Demonstrate ability to lead secure AI engineering at enterprise and multi-client scale • Strong balance of technical depth, risk judgment, and executive communication • Proven effectiveness operating in global, regulated, client-delivery environments • Credibility with both deeply technical teams and non-technical executive stakeholders
• Define and lead the Secure AI Engineering practice across enterprise and client-delivered AI solutions. • Establish secure-by-design standards, guardrails, and engineering controls for ML, GenAI, LLM, RAG, and Agentic AI systems • Translate regulatory and risk requirements into practical engineering standards aligned with business outcomes. • Oversee security architecture for the end-to-end AI lifecycle—data ingestion, training, fine-tuning, model management, inference, APIs, integrations, and infrastructure. • Ensure protection against advanced AI threats including data poisoning, model theft, prompt injection, inference attacks, agent misuse, hallucination exploitation, and supply-chain compromise. • Drive adoption of secure reference architectures, reusable components, and hardened AI pipelines across delivery teams. • Embed security controls into CI/CD, MLOps, and LLMOps pipelines to enable scale without friction. • Partner with cyber security and IR teams on AI-related incident preparedness, response, and post-incident improvements • Client Advisory & External Engagement • Act as a trusted advisor to business and clients on secure AI architecture, risk posture, and regulatory readiness. • Lead or support AI security reviews, architecture assessments, and risk discussions for strategic clients. • Build strong internal capability in secure AI engineering and adversarial ML awareness. solutions etc.
Masters DegBachelor’s or Master’s degree in Computer Science, Cyber Security, AI/ML, Data Science, or related field
10–15+ years of experience in cyber security, secure architecture, or platform engineering, with 3+ years focused on Agentic, AI/ML or GenAI environments
Strong hands-on understanding of cloud-based AI platforms (Azure, AWS, GCP or equivalent)
Experience or strong working knowledge of AI governance, privacy, and MLOps/LLMOps tooling (e.g., Credo.ai, Priva Sapien, model registries and monitoring tools)
Deep knowledge of Secure AI & adversarial ML, Privacy-by-design and data protection, Secure MLOps / LLMOps practices
Familiarity with frameworks and regulations such as NIST AI RMF, NIST CSF, ISO/IEC standards, Emerging global AI regulations (US, EU, sector-specific)
Experience supporting clients in highly regulated industries strongly preferred (preferred) 14 Years