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By mentoring Security and R&amp;D to define the MLSecOps roadmap, you&#39;ll ensure a &#39;secure-by-default&#39; future for agentic workflows and resilient AI innovation.</p>\n<p>Responsibilities:</p>\n<p>Serve as the primary subject matter expert for all AI and machine learning security initiatives across security and R&amp;D.</p>\n<p>Design and manage AI gateways to provide a centralized control plane for authentication and authorization and rate limiting across all model and tool interactions.</p>\n<p>Build and maintain an autonomous security agentic framework that utilizes multi agent orchestration for end to end investigation and alert triage and remediation.</p>\n<p>Develop agentic identity models using OAuth 2.1 to propagate identity across trust boundaries and prevent the confused deputy problem.</p>\n<p>Help govern the AI augmented software development lifecycle by integrating real time security gates into the developer environment and CI/CD pipeline.</p>\n<p>Manage Agentic Security Solutions that secure AI lifecycle and manage AI workloads at runtime.</p>\n<p>Author company wide AI security standards and implement these security checks across Twilio&#39;s stack.</p>\n<p>Implement human in the loop checkpoints and transactional safety protocols for high impact or destructive agentic actions.</p>\n<p>Partner with engineering leadership to set the long term roadmap for identity centric security and automated posture management.</p>\n<p>Act as a knowledge multiplier by mentoring security engineers and developing secure by default paved road templates for R&amp;D teams</p>\n<p>Qualifications:</p>\n<p>8+ years of experience in security engineering with at least 3 years focused on AI or machine learning security operations (MLSecOps).</p>\n<p>Expertise in orchestrating multi-agent systems with AWS Strands, LangGraph, and CrewAI, specializing in runtime isolation, PII redaction, and defending against indirect prompt injection in agentic environments.</p>\n<p>Hands-on experience with AI-specific frameworks (e.g., MITRE ATLAS, MAESTRO, OWASP Top 10 for LLMs/Agents/MCP) to threat model and defend against a wide spectrum of risks, including direct/indirect prompt injection, training data poisoning, tool poisoning, and data exfiltration within agentic workflows.</p>\n<p>Proficiency in securing end-to-end AI pipelines, from data ingestion and training to model deployment and monitoring.</p>\n<p>Strong communication skills to translate complex AI risks into actionable business logic for stakeholders.</p>\n<p>Desired:</p>\n<p>Hands-on experience in modern application security tooling including SAST and SCA and DAST with experience adapting these tools to catch AI specific vulnerabilities like indirect prompt injection.</p>\n<p>Expertise in identity standards including OAuth 2.1 and PKCE.</p>\n<p>Experience with AI Red Teaming and conducting adversarial simulations against Large Language Models (LLMs) and agentic systems.</p>\n<p>Proficiency in at least one general programming language (Python, Go, etc) with experience in container security and workload isolation.</p>\n<p>Proven ability to operate with autonomy and drive high impact outcomes in ambiguous environments by identifying and executing on critical projects without predefined roadmaps or direct supervision.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_0ae6f8dc-4fd","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Twilio","sameAs":"https://www.twilio.com/","logo":"https://logos.yubhub.co/twilio.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/twilio/jobs/7821462","x-work-arrangement":"remote","x-experience-level":"staff","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["security engineering","AI and machine learning security","multi-agent systems","AWS Strands","LangGraph","CrewAI","runtime isolation","PII redaction","indirect prompt injection","AI-specific frameworks","MITRE ATLAS","MAESTRO","OWASP Top 10 for LLMs/Agents/MCP","end-to-end AI pipelines","data ingestion","training","model deployment","monitoring","strong communication skills"],"x-skills-preferred":["modern application security tooling","SAST and SCA and DAST","identity standards","OAuth 2.1","PKCE","AI Red Teaming","adversarial simulations","Large Language Models","container security","workload isolation"],"datePosted":"2026-04-18T15:44:10.579Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Remote - 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In this role, you will be pivotal in helping define the strategy for creating the optimal customer experience when interacting with AI agents. You will implement this vision through targeted configuration of workflows and automations, regular reviews of bot performance and quality coaching.</p>\n<p>You&#39;ll sit at the intersection of customer experience, automation quality, and operational efficiency, partnering closely with Customer Support Strategy and Ops, Engineering, Product and external vendors to ensure the bot delivers a high-quality, safe, and trustworthy experience at scale.</p>\n<p>Along with the bot-focused work, you will be instrumental in defining the AI strategy within the CS org, creating best practices and supporting peers across CS in investigating AI solutions to maximise efficiency within the team.</p>\n<p>Key Responsibilities:</p>\n<ul>\n<li>Partner with CS and Product leadership to define the strategy and roadmap for our chatbot and email AI agents to contribute to company OKRs</li>\n<li>Architect and optimize AI agent workflows and procedures: Design simple, reliable conversation workflows and automations so our chatbot asks the right questions, clarifies common customer needs, and responds with accurate information, appropriately escalating to live support when needed.</li>\n<li>Quality reviews, analytics and bot coaching: Conduct regular reviews of bot conversations and high-level report analysis to identify trends, areas of opportunity and potential risk within the chatbot.</li>\n<li>Cross-collaboration to improve resolution rate and quality: Work with partners in Engineering, Product and CS Strategy and Ops to maximise the types of interactions the chatbot can support and resolve - connecting new data sources or systems on the backend to give the bot greater scope, implementing new workflows that use this data to solve new customers requests without live support intervention.</li>\n<li>Optimise the AI Agent experience across all channels: Expand upon the types of interactions and experiences that qualify for the email AI agent and other asynchronous channels.</li>\n<li>Compliance and security: Ensure Mercury&#39;s high standards for security and compliance are woven into the foundations of our AI-assisted CS strategy</li>\n<li>AI vendor relationship owner: Own the relationship with AI vendors for CS solutions, including Intercom. Raising issues, requesting fixes, staying on top of product releases and coordinating changes that impact CS operations</li>\n<li>Scoping of internal agent co-pilot: Drive efforts to assess and implement agent assist AI tools to maximise agent efficiency</li>\n<li>Evaluation of AI tooling for CS partners: Support other teams, such as Learning and Development and QA in evaluating how other tools&#39; AI offerings can increase efficiency across CS.</li>\n</ul>\n<p>What You Bring to the Table:</p>\n<ul>\n<li>1–3 years of experience in configuration of customer-facing AI agent/chatbot (e.g., Fin by Intercom, Ada, Zendesk AI)</li>\n<li>5+ years of experience in customer support backend operations or CS systems administration</li>\n<li>Systems thinker and problem solver, with experience in testing new solutions and change management for CS teams</li>\n<li>Strong technical acumen, with the ability to understand and communicate technical concepts to both technical and non-technical audiences</li>\n<li>Analytical thinking: ability to interpret data quickly and translate it into actionable decisions</li>\n<li>Cross-collaboration: works effectively with cross-functional partners across Engineering, Product, Compliance, Core Customer Support</li>\n<li>Stakeholder communication: delivers clear, concise updates to stakeholders at all levels</li>\n<li>Adaptability and a growth mindset, thriving in a fast-paced, ever-evolving environment</li>\n<li>Proven ability to work cross-functionally, particularly with technical teams like Engineering, Product, and Security</li>\n<li>An interest in software development or engineering, enabling deeper technical conversations with our engineering teams</li>\n<li>Experience with core customer support platforms such as Zendesk, Guru, MaestroQA/Rippit</li>\n<li>Proficiency in SQL and familiarity with navigating data tables</li>\n<li>Experience supporting remote or distributed workforce models</li>\n</ul>\n<p>The total rewards package at Mercury includes base salary, equity (stock options), and benefits.</p>\n<p>Our salary and equity ranges are highly competitive within the SaaS and fintech industry and are updated regularly using the most reliable compensation survey data for our industry. New hire offers are made based on a candidate&#39;s experience, expertise, geographic location, and internal pay equity relative to peers.</p>\n<p>Our target new hire base salary ranges for this role are the following:</p>\n<ul>\n<li>US employees in New York City, Los Angeles, Seattle, or the San Francisco Bay Area: $143,400 - $168,700 USD</li>\n<li>US employees outside of New York City, Los Angeles, Seattle, or the San Francisco Bay Area: $129,100 - $151,800 USD</li>\n<li>Canadian employees (any location): CAD $130,500 - $153,500</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_79078275-e22","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Mercury","sameAs":"https://www.mercury.com/","logo":"https://logos.yubhub.co/mercury.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/mercury/jobs/5888354004","x-work-arrangement":"remote","x-experience-level":"mid","x-job-type":"full-time","x-salary-range":"$143,400 - $168,700 USD (US employees in New York City, Los Angeles, Seattle, or the San Francisco Bay Area)","x-skills-required":["configuration of customer-facing AI agent/chatbot","customer support backend operations","CS systems administration","systems thinking","problem solving","technical acumen","analytical thinking","cross-collaboration","stakeholder communication","adaptability","growth mindset","SQL","data tables"],"x-skills-preferred":["software development","engineering","Zendesk","Guru","MaestroQA/Rippit"],"datePosted":"2026-04-17T12:45:26.554Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA, New York, NY, Portland, OR, or Remote within Canada or United States"}},"jobLocationType":"TELECOMMUTE","employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"configuration of customer-facing AI agent/chatbot, customer support backend operations, CS systems administration, systems thinking, problem solving, technical acumen, analytical thinking, cross-collaboration, stakeholder communication, adaptability, growth mindset, SQL, data tables, software development, engineering, Zendesk, Guru, MaestroQA/Rippit","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":143400,"maxValue":168700,"unitText":"YEAR"}}}]}