{"id":3461948,"url":"https://alion.io/job/ey-senior-ai-security-engineer","title":"Senior AI Security Engineer","company":{"id":2859,"name":"EY","domain":"ey.com","url":"https://alion.io/company/ey-com","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"SuccessFactors","truth_index":null},"role":"Security","role_family":"Security","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Taguig, Philippines"],"countries":["PH"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":21000,"max_usd":48000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":2372},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Azure","optional":false},{"name":"Embeddings","optional":false},{"name":"EU AI Act","optional":false},{"name":"Function Calling","optional":false},{"name":"Git","optional":false},{"name":"Human-in-the-Loop","optional":false},{"name":"Least Privilege","optional":false},{"name":"LLM","optional":false},{"name":"LLM Evaluation","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"Multi-Agent Systems","optional":false},{"name":"NIST AI RMF","optional":false},{"name":"OpenAI","optional":false},{"name":"OWASP","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Red Teaming","optional":false},{"name":"Threat Modeling","optional":false},{"name":"Azure AKS","optional":true},{"name":"Azure DevOps","optional":true},{"name":"DeepEval","optional":true},{"name":"Docker","optional":true},{"name":"Fine-tuning","optional":true},{"name":"Kubernetes","optional":true},{"name":"LangSmith","optional":true},{"name":"Machine Learning","optional":true},{"name":"MLFlow","optional":true},{"name":"Promptfoo","optional":true},{"name":"Ragas","optional":true}],"status":"live","first_seen_at":"2026-10-29T14:08:48Z","employer_posted_date":"2026-10-29","last_verified_at":"2026-11-02T20:49:19Z","board_verified":true,"closed_at":null,"days_open":4,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":4},"description":"Position Summary\nWe are seeking a Senior AI Security Engineer to assess and strengthen the security of enterprise Generative AI and agentic AI solutions.\nThe ideal candidate has an end-to-end understanding of GenAI application architecture, including Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), embeddings, vector databases, guardrails, AI agents, tools, memory, and Model Context Protocol (MCP).\nThis role will conduct AI threat modeling, security assessments, red-team testing, and automated security evaluations. The candidate should be technically hands-on and capable of building or modifying AI agents, RAG applications, APIs, MCP integrations, and security-testing automation.\nThe role will work closely with AI engineering, application security, cloud, privacy, risk, and governance teams to ensure that AI solutions are secure, resilient, and aligned with organizational requirements.\nKey Responsibilities\nReview and threat-model LLM, RAG, agentic AI, and multi-agent architectures.\nIdentify security risks across models, prompts, data sources, vector databases, memory, tools, APIs, and MCP integrations.\nDesign and validate security controls and guardrails for AI inputs, outputs, data access, tool execution, and autonomous actions.\nConduct AI security assessments and red-team testing for threats such as prompt injection, jailbreaks, sensitive-data disclosure, poisoning, excessive agency, unsafe tool use, and privilege abuse.\nAssess the security of MCP clients, servers, tools, resources, authorization, permissions, and third-party integrations.\nBuild automated security tests and evaluation harnesses for GenAI and agentic AI applications.\nValidate access controls, least-privilege implementation, human-approval mechanisms, secure secret handling, logging, and monitoring.\nIntegrate AI security testing into development and release processes.\nDocument security findings and provide clear, practical remediation recommendations.\nTranslate AI risk and governance requirements into appropriate technical controls.\nCollaborate with engineering and security teams to embed security throughout the AI development lifecycle.\nStay current with emerging GenAI threats, agentic AI attack techniques, MCP security risks, and defensive practices.\nRequired Skills and Experience\nStrong understanding of the end-to-end GenAI application lifecycle and its security risks.\nPractical knowledge of LLMs, prompt design, RAG, embeddings, vector databases, data-ingestion pipelines, and guardrails.\nHands-on experience building, integrating, testing, or securing AI agents and tool-enabled workflows.\nUnderstanding of agent planning, memory, tool execution, multi-agent workflows, and human-in-the-loop controls.\nKnowledge of MCP architecture, authorization, permissions, and security considerations.\nExperience conducting application security assessments, threat modeling, and security testing or red teaming.\nFamiliarity with current OWASP guidance for GenAI, LLM, and agentic applications.\nKnowledge of secure application architecture, API security, identity and access management, secrets management, and data protection.\nStrong hands-on Python scripting or development skills.\nExperience working with APIs, SDKs, authentication, Git, and automated testing.\nAbility to independently review, debug, test, and secure human-written and AI-generated code.\nExperience with Azure AI Foundry, Azure OpenAI, or comparable enterprise AI platforms.\nWorking knowledge of relevant AI risk and governance frameworks, including ISO/IEC 42001, the NIST AI Risk Management Framework and its Generative AI Profile, and the EU AI Act, with the ability to translate applicable requirements into technical controls.\nStrong written and verbal communication skills, including the ability to explain technical risks to business stakeholders.\nQualifications\nBachelor’s degree in Computer Science, Cybersecurity, Engineering, Information Technology, or a related discipline, or equivalent practical experience.\nFive or more years of relevant experience in cybersecurity, application security, software engineering, cloud security, AI engineering, or related fields.\nDemonstrated hands-on experience working with Generative AI or agentic AI solutions.\nStrong analytical, problem-solving, documentation, and stakeholder-management skills.\nPreferred Qualifications\nExperience developing AI security testing or evaluation frameworks.\nExperience with Promptfoo, DeepEval, Ragas, LangSmith, MLflow, or similar tools.\nExperience implementing or assessing AI security controls in regulated industries.\nExperience supporting ISO/IEC 42001, AI impact assessments, or EU AI Act compliance activities.\nFamiliarity with Azure security, Azure DevOps, Docker, Kubernetes, or AKS.\nKnowledge of model training, fine-tuning, adversarial machine learning, or AI supply-chain security.\nRelevant professional training or certification in cybersecurity, cloud security, AI security, or AI governance.","description_format":"text","description_chars":4979,"description_truncated":false,"requirements":{"experience_years_min":5,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Application Security","Financial Advisory, Valuation & Restructuring","Management Consulting","Tax Advisory & 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