Incident Manager Jobs

About the Team OpenAI’s User Operations team shepherds our customers’ adoption of AI and ensures that our customers' product experience is nothing short of exceptional. We are building the very first post-AGI support team. We resolve complex issues, provide technical guidance, and support customers in maximizing value and adoption from deploying our products. We work closely with Sales, Technical Success, Product, Engineering and others, to deliver the best possible experience to our customers at scale. OpenAI's customers represent a range of diverse backgrounds and maturity, from early-stage startups to established global enterprises. About the Role We’re looking for dedicated, experienced, and deeply curious individuals to help solve some of the most complex challenges faced by our customers while building the future of post-AGI support alongside us. In this role, you’ll work directly with customers through support tickets and live calls, troubleshooting high-impact issues and resolving novel, often ambiguous technical problems in one of the fastest-moving environments in technology. As AI adoption rapidly accelerates, the work you do will directly support mission-critical systems being built on OpenAI’s platform, serving as a critical line of defense for customers operating at massive scale. Beyond resolving technical issues, you’ll help define what world-class support looks like in an AGI-driven future. You’ll partner closely with Engineering, Product, and Operations to improve systems, reduce bugs, and elevate the customer experience, while leveraging automation, agents, and our own AI technology to transform how support operates at scale. You’ll be responsible for: Working directly with customers to troubleshoot and resolve their most complex technical issues, including API failures, integration challenges, authentication errors, and production incidents. Providing end-to-end ownership through debugging logs, analyzing system behavior, reproducing issues, and

Sr. Security Engineer, Corporate Security At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. Lyft connects people to transportation to change the way we live and get around our communities. Lyft’s engineering team is growing rapidly, and we are looking for Security Engineers to help us scale. Come be part of a new team at Lyft focused on enabling and empowering engineering teams to deliver at scale. Our drivers and passengers entrust Lyft with their personal information and travel details to get where they're going and expect us to keep that data safe. Lyft's security team leads efforts across the company to ensure our systems are secure and worthy of our users' trust. The security team designs and builds Lyft's security architecture, consult with other teams as they build and launch new products and features, proactively plans for the unexpected, and responds to incidents that occur. Our work affects the entire company and takes place at all levels of the stack, from infrastructure to web application security, as well as mobile apps, IT, and autonomous vehicles. We try to approach security from a software engineering standpoint. We believe in scaling security through automation and tooling and we ship frequently. Check out our blog posts at https://eng.lyft.com/tagged/security to learn more about some of the things we’ve built. We're looking for an engineer to own the security of the systems Lyft employees rely on every day: identity, endpoints, and the data that moves between them. Corporate Security sits where security meets IT, so the work spans detection engineering, platform operations, and the automation that ties them together. We'd rather write code than file tickets, and we measure ourselves on control coverage and time-to-remediate. If you want real ownership over how security works at company scale, this is that role. Responsibiliti

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic's production models undergo sophisticated post-training processes to enhance their capabilities, alignment, and safety. As a Research Engineer on our Post-Training team, you'll train our base models through the complete post-training stack to deliver the production Claude models that users interact with. You'll work at the intersection of cutting-edge research and production engineering, implementing, scaling, and improving post-training techniques like Constitutional AI, RLHF, and other alignment methodologies. Your work will directly impact the quality, safety, and capabilities of our production models. Note: For this role, we conduct all interviews in Python. This role may require responding to incidents on short-notice, including on weekends. Responsibilities: Implement and optimize post-training techniques at scale on frontier models Conduct research to develop and optimize post-training recipes that directly improve production model quality Design, build, and run robust, efficient pipelines for model fine-tuning and evaluation Develop tools to measure and improve model performance across various dimensions Collaborate with research teams to translate emerging techniques into production-ready implementations Debug complex issues in training pipelines and model behavior Help establish best practices for reliable, reproducible model post-training You may be a good fit if you: Thrive in controlled chaos and are energised, rather than overwhelmed, when juggling multiple urgent priorities Adapt quickly to changing priorities Maintain clarity when debugging complex, time-sensitive issues Have strong software en

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation. Our team includes creators of popular open-source projects (e.g., Seaborn , Luigi ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: At Modal, we sell cloud services atop which our customers run their critical production systems. As a rapidly growing new cloud infrastructure company, we seek to improve our reliability dramatically while scaling the size of our platform, customer base, and our team. This role is for people who are deep systems thinkers, love stacking nines, and thrive from making others move faster at scale. Responsibilities include: Identifying architectural changes to improve reliability and performance. Fostering a culture of reliability across Modal’s engineering organization. Defining and implementing operational processes such as deployments, upgrades, etc. Operating systems like Kubernetes, Postgres, Redis, etc. Participating in on-call rotations, and responding to production incidents. Requirements: 5+ years of experience writing high-quality production code. 2+ years of on-call experience for critical p

About the Team OpenAI’s User Operations team shepherds our customers’ adoption of AI and ensures that our customers' product experience is nothing short of exceptional. We are building the very first post-AGI support team. We resolve complex issues, provide technical guidance, and support customers in maximizing value and adoption from deploying our products. We work closely with Sales, Technical Success, Product, Engineering and others, to deliver the best possible experience to our customers at scale. OpenAI's customers represent a range of diverse backgrounds and maturity, from early-stage startups to established global enterprises. About the Role We’re looking for dedicated, experienced, and deeply curious individuals to help solve some of the most complex challenges faced by our customers while building the future of post-AGI support alongside us. In this role, you’ll work directly with customers through support tickets and live calls, troubleshooting high-impact issues and resolving novel, often ambiguous technical problems in one of the fastest-moving environments in technology. As AI adoption rapidly accelerates, the work you do will directly support mission-critical systems being built on OpenAI’s platform, serving as a critical line of defense for customers operating at massive scale. Beyond resolving technical issues, you’ll help define what world-class support looks like in an AGI-driven future. You’ll partner closely with Engineering, Product, and Operations to improve systems, reduce bugs, and elevate the customer experience, while leveraging automation, agents, and our own AI technology to transform how support operates at scale. You’ll be responsible for: Working directly with customers to troubleshoot and resolve their most complex technical issues, including API failures, integration challenges, authentication errors, and production incidents. Providing end-to-end ownership through debugging logs, analyzing system behavior, reproducing issues, and

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation. Our team includes creators of popular open-source projects (e.g., Seaborn , Luigi ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We are looking for strong engineers with experience and interest in designing, building, and maintaining the novel, high-performance systems that make up our serverless platform. Requirements: 5+ years of experience writing high-quality production code Experience building high-performance distributed systems at a large scale (the more battle scars, the better) Strong cloud skills Strong knowledge of low-level operating system foundations (Linux kernel, file systems, containers, etc.) Experience with performance engineering (tell us a story of when you shaved off a few milliseconds!) Ability to work in-person in our Stockholm office. Prior experience with Rust is nice to have, but not required. Ability to participate in on-call rotation and respond to production incidents.

Job Title: Aseptic Pharmacy Technician Banding: 5 Location: Bradford Start Date: ASAP End date: April Hourly Rate: £19-£21 Working Hours: 37.5 Job Overview We are seeking an experienced Aseptic Pharmacy Technician to join our team. The successful candidate will be responsible for the accurate preparation, assembly, and documentation of sterile medicinal products within an aseptic environment. This role ensures compliance with regulatory standards, aseptic technique, and quality assurance procedures to support safe and effective patient care. Key Responsibilities Prepare sterile pharmaceutical products, including intravenous admixtures, cytotoxic drugs, parenteral nutrition, and other aseptic preparations, in accordance with approved procedures. Operate within controlled cleanroom environments, maintaining strict aseptic technique and contamination control. Follow Standard Operating Procedures (SOPs), Good Manufacturing Practice (GMP), and relevant regulatory guidelines. Accurately label, check, and document all aseptic preparations. Perform routine cleaning, environmental monitoring, and equipment checks within aseptic areas. Participate in validation, media fills, and competency assessments as required. Assist in stock control, storage, and rotation of raw materials and consumables used in aseptic services. Identify, report, and document deviations, incidents, and near-misses in line with quality systems. Work collaboratively with pharmacists, technicians, and other healthcare professionals to meet service demands. Support training of new staff and contribute to continuous quality improvement initiatives. Qualifications and Experience Accredited Pharmacy Technician qualification (or equivalent). Registration with the relevant professional or regulatory body (where applicable). Previous experience working in an aseptic or cleanroom environment is highly desirable. Knowledge of aseptic techniques, GMP, and infection control principles. Why Choose Pulse? Competitive p

Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. Auth0 provides an unparalleled authentication experience for hundreds of millions of users worldwide. Our commitment to reliability is a key foundation of our product and our dedication to exceeding customer availability expectations is a core engineering focus. As a Senior Site Reliability Engineer, you'll join our SRE team based in Europe to ensure our production systems are not only operational but also resilient, scalable, and ready for exponential growth. This isn't just about keeping the lights on; it's about directly contributing to the platform's core resiliency and robustness. You'll be a hands-on builder, crafting solutions that make our system more reliable by design. What you’ll do: Design and build custom software in Go to enhance the platform's reliability, resiliency, and redundancy. Partner with engineering teams to embed reliability principles, improving the availability, performance, and observability of our services. Use your deep understanding of infrastructure and observability principles to identify opportunities for improvement within the product and implement solutions. Contribute to our follow-the-sun on-call rotation, providing rapid, effective response to critical incidents and using your expertise to troubleshoot, mitigate or accurately escalate production issues. Because our team is globally distributed, your on-call shifts will only occur during your standard local working hours. Develop and refine our SRE tooling and proc

About the Team The Applications Engineering team works across research, engineering, product, and design to bring OpenAI’s technology to consumers and businesses. You’ll join the team responsible for running the core infrastructure that supports products like ChatGPT and the API. The systems we support include our kubernetes clusters, infrastructure deployment, our networking stack, cloud abstractions, and more. We seek to learn from deployment and distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely. Safety is more important to us than unfettered growth. About the Role The cloud infrastructure team builds and maintains infrastructure abstractions allowing OpenAI to ship products quickly and scalably. In this role, you will: Design and build the development and production platforms that power our products, enabling reliability and security at scale Ensure our infrastructure can scale to the next order of magnitude Help create a diverse, equitable, and inclusive culture that makes all feel welcome while enabling radical candor and the challenging of group think Like all other teams, we are responsible for the reliability of the systems we build. This includes an on-call rotation to respond to critical incidents as needed. You might thrive in this role if you: Have 5+ years building core infrastructure Have experience operating orchestration systems such as Kubernetes at scale Have experience building abstractions over cloud platforms Take pride in building and operating scalable, reliable, secure systems Are comfortable with ambiguity and rapid change 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

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role: Anthropic's ML Performance and Scaling team trains our production pretrained models, work that directly shapes the company's future and our mission to build safe, beneficial AI systems. As a Research Engineer on this team, you'll ensure our frontier models train reliably, efficiently, and at scale. This is demanding, high-impact work that requires both deep technical expertise and a genuine passion for the craft of large-scale ML systems. This role lives at the boundary between research and engineering. You'll work across our entire production training stack: performance optimization, hardware debugging, experimental design, and launch coordination. During launches, the team works in tight lockstep, responding to production issues that can't wait for tomorrow. Responsibilities: Own critical aspects of our production pretraining pipeline, including model operations, performance optimization, observability, and reliability Debug and resolve complex issues across the full stack—from hardware errors and networking to training dynamics and evaluation infrastructure Design and run experiments to improve training efficiency, reduce step time, increase uptime, and enhance model performance Respond to on-call incidents during model launches, diagnosing problems quickly and coordinating solutions across teams Build and maintain production logging, monitoring dashboards, and evaluation infrastructure Add new capabilities to the training codebase, such as long context support or novel architectures Collaborate closely with teammates across SF and London, as well as with Tokens, Architectures, and Systems teams Contribute to

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role: Anthropic's ML Performance and Scaling team trains our production pretrained models, work that directly shapes the company's future and our mission to build safe, beneficial AI systems. As a Research Engineer on this team, you'll ensure our frontier models train reliably, efficiently, and at scale. This is demanding, high-impact work that requires both deep technical expertise and a genuine passion for the craft of large-scale ML systems. This role lives at the boundary between research and engineering. You'll work across our entire production training stack: performance optimization, hardware debugging, experimental design, and launch coordination. During launches, the team works in tight lockstep, responding to production issues that can't wait for tomorrow. Responsibilities: Own critical aspects of our production pretraining pipeline, including model operations, performance optimization, observability, and reliability Debug and resolve complex issues across the full stack—from hardware errors and networking to training dynamics and evaluation infrastructure Design and run experiments to improve training efficiency, reduce step time, increase uptime, and enhance model performance Respond to on-call incidents during model launches, diagnosing problems quickly and coordinating solutions across teams Build and maintain production logging, monitoring dashboards, and evaluation infrastructure Add new capabilities to the training codebase, such as long context support or novel architectures Collaborate closely with teammates across SF and London, as well as with Tokens, Architectures, and Systems teams Contribute to

About the Team The Applied Engineering team works across research, engineering, product, and design to bring OpenAI’s technology to consumers and businesses. You’ll join the team responsible for running the core infrastructure that supports products like ChatGPT and the API. The systems we support include our kubernetes clusters, infrastructure deployment, our networking stack, cloud abstractions, and more. We seek to learn from deployment and distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely. Safety is more important to us than unfettered growth. About the Role The cloud infrastructure team builds and maintains infrastructure abstractions allowing OpenAI to ship products quickly and scalably. This role is based in San Francisco, CA. In this role, you will: Design and build the development and production platforms that power our products, enabling reliability and security at scale Ensure our infrastructure can scale to the next order of magnitude Help create a diverse, equitable, and inclusive culture that makes all feel welcome while enabling radical candor and the challenging of group think Like all other teams, we are responsible for the reliability of the systems we build. This includes an on-call rotation to respond to critical incidents as needed. You might thrive in this role if you: Have 5+ years building core infrastructure Have experience operating orchestration systems such as Kubernetes at scale Have experience building abstractions over cloud platforms Take pride in building and operating scalable, reliable, secure systems Are comfortable with ambiguity and rapid change This role is exclusively based in our San Francisco HQ. We offer relocation assistance to new employees. 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 depl

Locations: South Jordan, UT Salary: $56,000 Launch Your Career in Technology Every app, website, payment, and digital service relies on technology running smoothly behind the scenes. When something goes wrong, Production Support Engineers are the people who investigate the issue, restore service, and help prevent it from happening again. If you're curious, analytical, and enjoy solving problems, this is an opportunity to build hands-on experience with cloud platforms, Linux, automation, databases, and large-scale enterprise systems from day one. What Is Production Support? Production Support Engineers keep business-critical applications running reliably in live environments. Think of it this way: Software Engineers build the platform. QA Engineers test the platform. Production Support Engineers keep the platform running when it matters most. Working at the intersection of technology and business, you'll troubleshoot issues, automate processes, and help improve the reliability and performance of systems used by thousands, or even millions, of people every day. If you enjoy solving puzzles, working under pressure, and understanding how large-scale systems work, this could be the perfect place to start your career. What You'll Do As part of a global production engineering team, you'll: Help support large-scale applications and platforms used by leading organizations around the world. Monitor business-critical applications and services to ensure high availability and performance. Investigate and resolve production incidents across applications, infrastructure, databases, and cloud environments. Analyse logs, alerts, and system metrics to identify root causes and prevent recurring issues. Partner with software engineers, infrastructure teams, and business stakeholders to improve system reliabilit

Job Title: Theatre Scrub Nurse/Practitioner – Ophthalmic Banding: 5 Location: Leeds Rate: £32.50 – £43.24 per hour Pulse Nursing is seeking a dedicated and experienced Theatre Scrub Nurse/Practitioner to support ophthalmic procedures at a leading NHS Trust. This role is available exclusively to candidates with scrub experience who can commit to set working days (Monday to Friday). Ophthalmic experience is preferred, but training can be provided. Key Responsibilities: • Provide scrub support for ophthalmic procedures in a sterile environment • Deliver patient care throughout the surgical pathway—from admission to discharge • Administer medicines and maintain documentation in line with NMC guidelines • Prepare, check and store theatre equipment appropriately • Assist with inventory and stock control, maintaining safe levels • Adhere to clinical governance policies, including reporting incidents when necessary • Maintain confidentiality in line with data protection legislation • Collaborate with the ophthalmic team and participate in ALS training • Take part in on-call and weekend rotas, and offer support at nearby clinics Requirements: • Registered Nurse with a valid NMC pin • Previous scrub experience, ideally within ophthalmics • Sound understanding of infection control and safe practice protocols • Effective communication and teamworking skills • Proficiency in Microsoft Office • Commitment to professional development Benefits: • Competitive weekly pay • £500 Refer a Friend bonus • Dedicated support from experienced consultants • Flexible work arrangements • Access to exclusive opportunities through Pulse’s preferred supplier status How to Apply: If y

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic's production models undergo sophisticated post-training processes to enhance their capabilities, alignment, and safety. As a Research Engineer on our Post-Training team, you'll train our base models through the complete post-training stack to deliver the production Claude models that users interact with. You'll work at the intersection of cutting-edge research and production engineering, implementing, scaling, and improving post-training techniques like Constitutional AI, RLHF, and other alignment methodologies. Your work will directly impact the quality, safety, and capabilities of our production models. Note: For this role, we conduct all interviews in Python. This role may require responding to incidents on short-notice, including on weekends. Responsibilities: Implement and optimize post-training techniques at scale on frontier models Conduct research to develop and optimize post-training recipes that directly improve production model quality Design, build, and run robust, efficient pipelines for model fine-tuning and evaluation Develop tools to measure and improve model performance across various dimensions Collaborate with research teams to translate emerging techniques into production-ready implementations Debug complex issues in training pipelines and model behavior Help establish best practices for reliable, reproducible model post-training You may be a good fit if you: Thrive in controlled chaos and are energised, rather than overwhelmed, when juggling multiple urgent priorities Adapt quickly to changing priorities Maintain clarity when debugging complex, time-sensitive issues Have strong softwa