- Demonstrated 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
TDefine 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
About UsSkills Required
- Bachelor's or Master's degree in Computer Science, Cybersecurity, AI/ML, Data Science, or a related field
- 10–15+ years of experience in cybersecurity, secure architecture, or platform engineering
- At least 3 years of experience focused on Agentic AI, AI/ML, or GenAI environments
- Hands-on understanding of cloud-based AI platforms such as Azure, AWS, or GCP
- Experience or strong working knowledge of AI governance, privacy, and MLOps/LLMOps tooling
- Deep knowledge of secure AI, adversarial ML, privacy-by-design, data protection, and secure MLOps/LLMOps practices
- Familiarity with NIST AI RMF, NIST CSF, ISO/IEC standards, and emerging global AI regulations
- Experience supporting clients in highly regulated industries
- 14 years of experience
EXL Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about EXL and has not been reviewed or approved by EXL.
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Healthcare Strength — Medical plan options include HSA, HRA, and PPO choices, with additional health-related programs such as disability coverage and an employee assistance program. Feedback suggests these options provide meaningful flexibility and coverage breadth for many roles.
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Leave & Time Off Breadth — Up to 20 days of paid time off, plus federal holidays and paid sick and safe time, are highlighted. Feedback suggests this leave structure is a notable benefit alongside core compensation.
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Retirement Support — A traditional and Roth 401(k) with up to a 3% company match and full vesting after one year is described. Feedback suggests this match and vesting timeline help bolster long-term savings.
EXL Insights
What We Do
Choosing a digital partner is about more than capabilities — it’s about collaboration and character. Unrealistic overhauls and off-the-shelf products ignore what matters most — your unique needs, culture, goals, and your legacy data and technology environments. At EXL, our collaboration is built on ongoing listening and learning to adapt our methodologies. We’re your business evolution partner—tailoring solutions that make the most of data to make better business decisions and drive more intelligence into your increasingly digital operations. Whether your goals are scaling the use of AI and digital, redesign operating models, or driving better and faster decisions, we’re here to partner with you to help you gain—and maintain—competitive advantage with efficient, sustainable models at scale. Our expertise in transformation, data science, and change management helps make your business more efficient and effective, improve customer relationships and enhance revenue growth. Instead of focusing on multi-year, resource- and time-intensive platform designs or migrations, we look deeper at your entire value chain to integrate strategies with impact. We use our specialization in analytics, digital interventions, and operations management—alongside deep industry expertise — to deliver solutions that help you outperform the competition. At EXL, it’s all about outcomes—your outcomes—and delivering success on your terms. Share your goals with us and together, we’ll optimize how you leverage data to drive your business forward. For more information, visit www.exlservice.com.
