# Engineering Manager, Guardian **Company:** [OpenAI](https://scaleengineer.com/companies/openai) Lead and grow OpenAI's Guardian team in London, overseeing the design and deployment of production systems that evaluate agent behavior, detect safety risks, and implement appropriate safeguards. This builder-manager role combines hands-on technical leadership with strategic team development, requiring expertise in AI agent systems, production infrastructure, and cross-functional collaboration between engineering, alignment research, and product teams. **Role:** Engineering Manager **Seniority:** Manager **Locations:** London, UK **Salary:** 220000–320000 GBP [Apply](https://jobs.ashbyhq.com/openai/a02f6f9c-2006-41db-b9b3-04654f8dfd5a) Canonical: https://scaleengineer.com/jobs/openai/engineering-manager-guardian --- ## Responsibilities - Team Leadership and Development: Lead, hire, and develop a London-based engineering team spanning agent safety, backend systems, applied AI, and product infrastructure. Establish a high-performing team culture, manage performance, provide coaching, and create clear career development pathways for direct reports. - Technical Roadmap and Strategy: Set and execute the technical roadmap for Auto-review and the broader Guardian platform, balancing critical safety requirements with product utility, latency constraints, and operational reliability. Make architectural decisions and prioritize engineering work across the team. - Production Safety Systems Development: Lead the design and implementation of production systems that evaluate agent actions in real-time, detect potentially harmful behavior, and enable safe recovery or escalation paths. Ensure systems scale reliably while maintaining safety guarantees. - User Intent and Context Understanding: Improve Guardian's ability to understand user intent, environmental context, permission boundaries, and personalization signals while maintaining privacy and minimizing user friction. Balance comprehensive oversight with streamlined user experiences. - Research-to-Product Translation: Partner closely with alignment researchers and product teams to convert prototypes, evaluations, and emerging monitoring techniques into scalable, dependable product capabilities. Communicate effectively across technical disciplines and translate open-ended research into engineering plans. - Cross-Functional Integration: Work across Product, Security, Infrastructure, and other engineering teams to integrate Guardian capabilities seamlessly into agent experiences throughout OpenAI's product ecosystem. Serve as the technical bridge between safety systems and operational requirements. - Evaluation and Operational Excellence: Establish rigorous evaluation and operational practices including adversarial testing, failure analysis, comprehensive monitoring, and quantitative metrics for safety performance, false positive rates, latency, and user impact. Create feedback loops for continuous improvement. - Hands-on Technical Contribution: Remain deeply involved in architecture decisions, design reviews, debugging complex problems, and writing code when it provides the highest leverage for team progress. Model technical excellence and maintain credibility through active contribution. ## Requirements ### education - {"name":"Computer Science Foundation","description":"Bachelor's degree in Computer Science, Software Engineering, or equivalent advanced technical education demonstrating strong fundamentals in algorithms, systems design, and software architecture."} ### technical - {"name":"AI Agent Systems Architecture","description":"Proven experience building with AI agents or large language models in production environments. Deep understanding of agentic system design patterns, challenges, failure modes, and the unique considerations for autonomous decision-making systems."} - {"name":"Production Systems at Scale","description":"Experience architecting and shipping complex, high-stakes production systems end-to-end. Expertise in system reliability, performance optimization, real-time evaluation systems, and operational monitoring at production scale."} - {"name":"Backend and Infrastructure Design","description":"Strong background in backend system design, distributed systems concepts, and infrastructure engineering. Ability to evaluate tradeoffs between latency, throughput, consistency, and operational complexity."} - {"name":"Safety-Critical System Development","description":"Experience building systems where correctness and safety are paramount. Understanding of failure analysis methodologies, adversarial testing, monitoring strategies, and risk mitigation in high-stakes environments."} - {"name":"Machine Learning Systems Integration","description":"Hands-on experience integrating machine learning models into production systems. Understanding of model evaluation, monitoring for model drift, and operational challenges of ML-powered decision systems."} ### experience - {"name":"Engineering Leadership Experience","description":"Minimum 5+ years of experience leading engineering teams that have shipped complex production systems. Demonstrated ability to hire, develop, coach, and manage high-performing engineers with a thoughtful management system."} - {"name":"Technical Leadership and Hands-on Contribution","description":"Proven ability to balance hands-on technical work with management responsibilities. Track record of making high-impact architectural decisions, conducting effective design reviews, and remaining technically credible in specialized domains."} - {"name":"Cross-Functional Collaboration","description":"Significant experience working effectively with research teams, product management, and security organizations. Ability to translate research findings and product requirements into clear engineering strategies and execution plans."} - {"name":"Product-Engineering Judgment","description":"Demonstrated ability to navigate complex tradeoffs between safety, usability, performance, and reliability. Experience making pragmatic decisions that balance competing constraints while maintaining architectural integrity."} ## Skills ### required - {"name":"Engineering Leadership","description":"Proven ability to lead, hire, develop, and manage engineering teams shipping production systems. Strong track record in performance management, technical hiring, and creating high-performing team cultures."} - {"name":"AI Agent Architecture","description":"Deep expertise in designing systems that work with autonomous agents. Understanding of agent decision-making frameworks, safety constraints, and operational considerations unique to agentic systems."} - {"name":"Production System Design","description":"Expertise in architecting scalable, reliable production systems. Strong understanding of distributed systems, performance optimization, monitoring, and operational best practices."} - {"name":"Safety-Critical Systems Engineering","description":"Experience building systems where correctness and harm prevention are critical. Familiarity with adversarial testing methodologies, risk assessment, and safety-focused monitoring and alerting."} - {"name":"Cross-Functional Communication","description":"Ability to communicate effectively with research scientists, product managers, security teams, and other engineering disciplines. Skill in translating between technical and non-technical stakeholders."} - {"name":"Research-to-Engineering Translation","description":"Proven ability to take open-ended research findings and prototype implementations, then develop them into scalable, production-ready systems with clear requirements and success metrics."} ### preferred - {"name":"Large Language Model Experience","description":"Hands-on experience working with large language models in production settings. Understanding of LLM capabilities, limitations, and operational considerations in deployed systems."} - {"name":"Safety and Security System Design","description":"Experience building safety-focused systems, security infrastructure, or other systems where preventing harm is a primary design goal. Familiarity with threat modeling and risk assessment frameworks."} - {"name":"Real-time Systems Development","description":"Experience building low-latency systems where response time is critical. Understanding of real-time constraints and optimization techniques for time-sensitive operations."} - {"name":"Evaluation Framework Development","description":"Experience creating comprehensive evaluation frameworks, metrics systems, and monitoring dashboards. Familiarity with defining success metrics in ambiguous or complex domains."} - {"name":"Startup or Fast-Growth Environment Experience","description":"Background in startup environments or rapid-growth phases of companies. Experience building teams and systems under uncertain requirements and evolving priorities."} - {"name":"UK Tech Ecosystem Experience","description":"Familiarity with London's tech scene and experience working in UK-based organizations. Understanding of UK employment practices and tech culture an advantage."} ## Tech stack ### tools - {"name":"Kubernetes or Container Orchestration","description":"Infrastructure for deploying and scaling safety evaluation services reliably across multiple regions and handling variable load."} - {"name":"Git and Version Control","description":"Standard version control for managing codebase, code review processes, and collaborative development across the engineering team."} - {"name":"CI/CD Pipelines","description":"Automated testing, deployment, and rollout systems. Critical for maintaining safety and reliability in production safety systems."} - {"name":"Monitoring and Observability (Datadog, Prometheus, etc.)","description":"Comprehensive monitoring, alerting, and observability infrastructure for tracking system health, safety metrics, false positive rates, and operational performance."} - {"name":"Incident Management and On-Call Tools","description":"Tools for coordinating incident response and on-call rotations. Essential for managing production safety systems where issues require immediate attention."} ### others - {"name":"Evaluation Frameworks and Methodologies","description":"Familiarity with A/B testing, adversarial testing frameworks, and statistical evaluation methods. Critical for establishing rigorous evaluation practices for safety systems."} - {"name":"OpenAI API and Product Ecosystem","description":"Understanding of OpenAI's product offerings, APIs, and agent capabilities. Knowledge of how Guardian systems integrate across OpenAI's product platform."} - {"name":"Alignment and Safety Research Concepts","description":"Exposure to AI alignment literature, safety evaluation techniques, and monitoring methodologies. Ability to understand and translate research concepts into engineering requirements."} ### databases - {"name":"PostgreSQL","description":"Likely primary relational database for storing agent interactions, safety decisions, audit logs, and evaluation metrics."} - {"name":"Redis or Similar Cache","description":"In-memory caching layer for low-latency access to user context, permissions, and frequently accessed evaluation data."} - {"name":"Time-Series Database","description":"Specialized database for monitoring safety metrics, system performance, and operational health tracking over time."} ### languages - {"name":"Python","description":"Primary language for AI systems, backend development, and integration with machine learning frameworks. Expected proficiency for system design and code review."} - {"name":"TypeScript/JavaScript","description":"Likely used in product infrastructure and agent-facing systems. Important for cross-platform system integration and understanding of broader OpenAI product architecture."} - {"name":"C++ or Rust","description":"Possible use in performance-critical components or system infrastructure. Beneficial familiarity for optimizing latency-sensitive safety evaluation systems."} ### frameworks - {"name":"FastAPI or Django","description":"Backend web framework for building scalable API services that handle agent evaluation requests and safety decision systems."} - {"name":"PyTorch or TensorFlow","description":"Machine learning frameworks for integrating model-based evaluations into production systems. Understanding of model serving and inference optimization."} - {"name":"Async/Concurrent Processing Frameworks","description":"Frameworks enabling high-throughput, low-latency processing of agent requests. Critical for real-time safety evaluation systems."} ## Benefits ### benefits - {"name":"Equity Ownership","description":"Competitive stock options providing meaningful ownership stake in OpenAI's future, with vesting aligned to long-term contribution."} - {"name":"Comprehensive Health Coverage","description":"Medical, dental, and vision insurance for employee and dependents. Includes mental health and wellness benefits supporting physical and psychological wellbeing."} - {"name":"Generous Paid Leave","description":"Competitive holiday allowance exceeding UK statutory requirements, plus flexible sick leave and sabbatical options for long-serving employees."} - {"name":"Professional Development Budget","description":"Annual allocation for conferences, courses, certifications, and professional development opportunities to maintain technical expertise and leadership skills."} - {"name":"Workplace Flexibility","description":"Flexible working arrangements with emphasis on in-office collaboration in London. Potential for remote days pending team and project requirements."} - {"name":"Parental and Family Support","description":"Competitive parental leave policies, childcare support, and family-friendly benefits. Resources for work-life balance and family planning."} - {"name":"Commuter and Transportation Benefits","description":"Support for London commuting including potential travel allowances, parking, or public transportation subsidies for the London office location."} - {"name":"Retirement Planning","description":"Workplace pension scheme aligned with UK regulations, with employer contributions supporting long-term financial security."} - {"name":"Learning and Knowledge Resources","description":"Access to industry research, technical books, industry subscriptions, and internal knowledge sharing systems. Support for staying current with emerging AI and safety research."} - {"name":"Mission-Driven Work Environment","description":"Opportunity to work on critical AI safety challenges with direct impact on responsible AI deployment. Access to cutting-edge research and collaboration with world-class AI researchers and engineers."} ## Compensation - **max:** 320000 - **min:** 220000 - **currency:** GBP - **stockOptions:** true ## Interview process ### steps - {"name":"Initial Screening Call","description":"30-minute conversation with the recruiting team to assess background, motivation, and alignment with the Guardian team's mission. Review of your experience with AI systems, team leadership, and product-engineering judgment."} - {"name":"Technical Leadership Discussion","description":"60-minute conversation with the hiring manager focusing on your experience leading engineering teams, specific examples of complex systems you've shipped, and how you've navigated technical tradeoffs in production environments."} - {"name":"System Design and Architecture Interview","description":"90-minute deep-dive into designing a safety-critical system. You'll work through an agent oversight or safety evaluation architecture, discussing tradeoffs between latency, accuracy, scalability, and operational reliability."} - {"name":"Research Collaboration Case Study","description":"60-minute discussion about translating research into production systems. You'll be presented with a research prototype or finding related to agent safety and asked how you'd productionize it, define requirements, and work with research teams."} - {"name":"Cross-Functional Collaboration Scenario","description":"45-minute conversation exploring how you'd handle competing priorities between product, safety, security, and research. Real scenarios you might encounter balancing safety, user experience, and system performance."} - {"name":"Team Leadership and Culture Discussion","description":"60-minute conversation with the current Guardian team lead or senior engineer about your approach to hiring, team development, performance management, and creating high-performing engineering cultures."} - {"name":"Final Executive Round","description":"30-minute conversation with a senior leader at OpenAI to discuss long-term vision, organizational fit, and your perspectives on AI safety and responsible deployment."} ## Full description **About the Team** The Guardian team builds practical safety and oversight systems for increasingly capable AI agents. Our goal is to make it possible for agents to take on longer-running, higher-autonomy work while preserving meaningful safeguards, respecting user intent, and intervening when actions could cause serious or difficult-to-reverse harm. Auto-review is an early example of this work. When an agent reaches a permission boundary, a separate model evaluates the proposed action in context and determines whether it should proceed. The team is now extending this foundation into more capable oversight systems that account for richer user context, support a broader range of agent experiences, and integrate across OpenAI products. Guardian sits at the intersection of engineering, alignment research, product, infrastructure, and security. The team already has a strong engineering foundation in London and will continue to grow there as a concentrated, highly collaborative group. **About the Role** We are looking for an Engineering Manager to lead and grow the Guardian team in London. You will own the engineering strategy and execution for production systems that evaluate agent behavior, identify risk, and take appropriate action without creating unnecessary friction for users. This is a builder-manager role with substantial technical depth. You will set direction, develop engineers, and create the operating cadence for a high-performing team, while remaining close enough to the work to shape architecture, review designs, debug difficult problems, and write code when it is the highest-leverage way to help the team move forward. The role is highly visible and cross-functional. You will work closely with alignment researchers to translate emerging research into dependable systems, and with product teams to make agent safety a foundational capability across OpenAI. This role is based in our London office. **In this role, you will** * Lead, hire, and develop a London-based team of engineers working across agent safety, backend systems, applied AI, and product infrastructure. * Set the technical roadmap for Auto-review and the broader Guardian platform, balancing safety, product utility, latency, and operational reliability. * Build production systems that evaluate agent actions in real time, detect potentially harmful behavior, and support safe recovery or escalation paths. * Improve how oversight systems understand user intent, environmental context, permissions, and relevant personalization signals while protecting privacy and avoiding unnecessary friction. * Partner closely with alignment researchers to turn prototypes, evaluations, and new monitoring techniques into scalable product capabilities. * Work across Product, Security, Infrastructure, and other engineering teams to integrate Guardian capabilities into agent experiences throughout OpenAI. * Establish rigorous evaluation and operational practices, including adversarial testing, failure analysis, monitoring, and metrics for safety performance, false positives, latency, and user impact. **You might thrive in this role if you** * Have significant experience leading engineering teams that shipped complex, high-stakes production systems end to end. * Have built with AI agents or large language models in a core product, startup, or technically serious independent project, and understand the unique challenges of agentic systems. * Bring strong product-engineering judgment and can navigate tradeoffs across safety, usability, speed, and reliability. * Can partner effectively with research teams, translate open-ended findings into engineering plans, and communicate clearly across technical disciplines. * Have a thoughtful management system for hiring, coaching, performance, and execution. * Care deeply about building AI systems that are useful, trustworthy, and safe. **About OpenAI** OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see [OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement](https://cdn.openai.com/policies/eeo-policy-statement.pdf). Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. 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