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We are looking for an AI Security Engineer to secure our AI-driven systems, including LLM-based applications, machine learning models, and AI-enabled automation tools. This role will focus on identifying, assessing, and mitigating security risks across the AI lifecycle — from model development and training to deployment and runtime monitoring. The ideal candidate combines strong security engineering experience with a deep understanding of machine learning systems and emerging AI-specific threats (e.g., prompt injection, model poisoning, data leakage, adversarial attacks). Key Responsibilities: AI/ML Security Architecture Design and implement security controls for AI/ML systems across development, training, and production Secure LLM integrations, RAG pipelines, and AI APIs Conduct threat modeling for AI systems and data pipelines Define secure-by-design patterns for AI-powered features AI Threat Detection & Mitigation Identify and mitigate AI-specific threats: prompt injection and jailbreak techniques, model poisoning and data contamination, adversarial attacks, training data leakage, insecure model serialization, excessive permissions in AI agents Develop guardrails, content filters, and output validation mechanisms Implement monitoring for anomalous AI behavior Secure Development & DevSecOps Integrate AI security checks into CI/CD pipelines Perform security reviews of ML code and AI-related infrastructure Secure model registries and artifact storage Collaborate with other engineers and platform teams to enforce security standards Data Protection & Compliance Ensure AI systems comply with: GDPR and data privacy regulations, financial industry regulatory requirements, implement controls for sensitive data used in training and inference, perform AI risk assessments aligned with internal risk methodology Governance & Policy Contribute to AI security standards and internal policies Define AI risk classification and control frameworks Support security reviews for new AI initiatives / tools Required Qualifications: 3-5+ years in software engineering, ML engineering, or application security Hands-on experience with AI/ML systems — LLMs, NLP models, or similar Python proficiency for automation and scripting Experience working with Claude Code Strong understanding of cloud platforms: AWS, Azure, or GCP Experience with API security, Docker, Kubernetes Knowledge of AI-specific security risks and mitigations Experience conducting threat modeling and risk assessments Preferred Qualifications: Familiarity with RAG architectures, vector databases, ML pipelines (MLflow, Kubeflow, SageMaker) Experience in fintech or regulated environments Knowledge of AI governance frameworks (EU AI Act, NIST AI RMF, ISO/IEC 42001) Experience with AI red teaming Background in cybersecurity or application security (OWASP, Secure SDLC) Soft Skills: Strong analytical and problem-solving skills Ability to translate technical risk into business impact Able to explain AI security risks and mitigations to non-security teams Cross-functional collaboration with ML, data, and product teams Clear documentation and communication skills What you will get in return: Competitive Salary: We believe great work deserves great pay! Your skills and talents will be rewarded with a salary that makes you feel valued and motivated Work-Life Harmony: Join a company that genuinely cares about you - because your life outside of work matters just as much as your time on the clock Generous Time Off: Need a breather? Our annual leave policy lets you recharge and enjoy life outside of work without a worry Employee Referral Program: Love working here? Share the love! Bring your talented friends on board and get rewarded for growing our awesome team Comprehensive Health & Pension Benefits: From medical insurance to pension plans, we’ve got your back. Plus, location-specific benefits and perks! Workation Wonderland: Live your digital nomad dreams with 30 extra days to work remotely from anywhere in the world (some restrictions apply). Adventure awaits! Volunteer Days: Make a difference! Take two additional paid days each year to support causes you care about and give back to the community Be a key player at the forefront of the digital assets movement, propelling your career to new heights! Join a dynamic and rapidly expanding company that values and rewards talent, initiative, and creativity. Work alongside one of the most brilliant teams in the industry. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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.