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- Job Description: Demonstrated ability to lead secure AI engineering at enterprise and multi-client scale - Robust 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 Responsibilities: 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 lifecycledata 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. Qualifications: Masters DegBachelors or Masters degree in Computer Science, Cyber Security, AI/ML, Data Science, or related field 1015+ years of experience in cyber security, secure architecture, or platform engineering, with 3+ years focused on Agentic, AI/ML or GenAI environments Solid 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 .
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.