Jobs in United States

Deployment Lead in United States

636 active opportunities · Updated October 2026

Explore current deployment lead jobs across United States. Filter by work mode, employment type, experience, department, date posted and distance.

C
📍 United States· Full-time
✓ Quality checkedCompany trend -100%

At ClickUp, we're building the future of work: the first truly converged AI workspace unifying tasks, docs, chat, calendar, and enterprise search, all supercharged by context-driven AI. We are an AI-native company. Every team member is expected to leverage AI daily, and we evaluate AI fluency as part of our hiring process. Join us and help redefine what's possible. 🚀 Role Overview: We are seeking a skilled and experienced Senior AI Engineer – AI Platform to join our ClickUp Engineering team. In this role, you will play a critical part in both building the core AI platform and directly applying large language models (LLMs) to deliver intelligent features across ClickUp. You will focus on backend systems that enable scalable, reliable, and secure AI-powered capabilities, while also working hands-on with LLMs to solve real user problems and drive product innovation. Key Responsibilities: Architect, design, and implement scalable AI platform services that support the deployment, orchestration, and lifecycle management of LLMs and other AI models. Apply LLMs and other AI technologies directly to build and enhance ClickUp’s intelligent features, working closely with product and engineering teams to deliver impactful solutions. Build and maintain robust APIs and backend systems that enable seamless integration of AI-powered features into ClickUp’s core platform. Develop infrastructure for model serving, monitoring, logging, and automated evaluation to ensure high reliability and performance of AI services in production. Integrate with multiple LLM providers (e.g., OpenAI, Anthropic, Google) and manage model selection, routing, and fallback strategies for optimal performance and cost. Drive the adoption of best practices in AI privacy, security, and compliance, including data anonymization, secure data handling, and regulatory adherence. Optimize platform performance, scalability, and cost-efficiency, leveraging cloud-native technologies and distributed systems. Stay curre

TypeScriptPythonAWSAzure
C
📍 United States· Full-time
✓ Quality checkedCompany trend -100%

At ClickUp, we're building the future of work: the first truly converged AI workspace unifying tasks, docs, chat, calendar, and enterprise search, all supercharged by context-driven AI. We are an AI-native company. Every team member is expected to leverage AI daily, and we evaluate AI fluency as part of our hiring process. Join us and help redefine what's possible. 🚀 Role Overview: We are seeking a highly skilled Staff AI Engineer – AI Platform to join our ClickUp Engineering team. In this role, you will play a critical part in both building the core AI platform and directly applying large language models (LLMs) to deliver intelligent features across ClickUp. You will focus on backend systems that enable scalable, reliable, and secure AI-powered capabilities, while also working hands-on with LLMs to solve real user problems and drive product innovation. Key Responsibilities: Architect, design, and implement scalable AI platform services that support the deployment, orchestration, and lifecycle management of LLMs and other AI models. Apply LLMs and other AI technologies directly to build and enhance ClickUp’s intelligent features, working closely with product and engineering teams to deliver impactful solutions. Build and maintain robust APIs and backend systems that enable seamless integration of AI-powered features into ClickUp’s core platform. Develop infrastructure for model serving, monitoring, logging, and automated evaluation to ensure high reliability and performance of AI services in production. Integrate with multiple LLM providers (e.g., OpenAI, Anthropic, Google) and manage model selection, routing, and fallback strategies for optimal performance and cost. Drive the adoption of best practices in AI privacy, security, and compliance, including data anonymization, secure data handling, and regulatory adherence. Optimize platform performance, scalability, and cost-efficiency, leveraging cloud-native technologies and distributed systems. Stay current with ad

TypeScriptPythonAWSAzure
R
📍 Foster City, California, United States· Full-time
✓ Quality checkedCompany trend -85.9%

Replit is the agentic software creation platform that enables anyone to build applications using natural language. With millions of users worldwide, Replit is democratizing software development by removing traditional barriers to application creation. About the Role Join our Enterprise Platform team and build the infrastructure foundations that enable the world's largest organizations to run Replit within their security and compliance boundaries. As a Software Engineer on this team, you'll design and implement the deployment flexibility, networking capabilities, authorization systems, and data controls that enterprises require, from single-tenant architectures and private connectivity to custom policy enforcement and customer-managed encryption. You'll work at the intersection of cloud infrastructure and enterprise requirements, partnering with Platform Engineering, Security, and Sales to ship capabilities that unlock adoption at demanding organizations. What You'll Do Build enterprise deployment infrastructure: Design and implement single-tenant and dedicated deployment options, enabling customers to run Replit with the isolation guarantees their security posture requires. Implement private networking capabilities: Build VPC peering, private connectivity, and static IP configurations that allow enterprises to integrate Replit into their existing network architectures. Design authorization services: Build the authorization infrastructure that enforces custom enterprise policies; enabling fine-grained access controls, custom permission models, and policy enforcement that integrates with customers' existing identity and governance systems. Ship data protection features: Implement bring-your-own-key (BYOK) encryption, customer-managed keys, and data residency controls that give enterprises ownership over their most sensitive data. Develop infrastructure automation: Write Terraform modules and automation that enable reliable, repeatable enterprise deployments across reg

TypeScriptPythonGCPKubernetes
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📍 Foster City, California, United States· Full-time
✓ Quality checkedCompany trend -85.9%

Replit is the agentic software creation platform that enables anyone to build applications using natural language. With millions of users worldwide, Replit is democratizing software development by removing traditional barriers to application creation. About the Role Join our Enterprise Platform team and build the infrastructure foundations that enable the world's largest organizations to run Replit within their security and compliance boundaries. As a Software Engineer on this team, you'll design and implement the deployment flexibility, networking capabilities, authorization systems, and data controls that enterprises require, from single-tenant architectures and private connectivity to custom policy enforcement and customer-managed encryption. You'll work at the intersection of cloud infrastructure and enterprise requirements, partnering with Platform Engineering, Security, and Sales to ship capabilities that unlock adoption at demanding organizations. What You'll Do Build enterprise deployment infrastructure: Design and implement single-tenant and dedicated deployment options, enabling customers to run Replit with the isolation guarantees their security posture requires. Implement private networking capabilities: Build VPC peering, private connectivity, and static IP configurations that allow enterprises to integrate Replit into their existing network architectures. Design authorization services: Build the authorization infrastructure that enforces custom enterprise policies; enabling fine-grained access controls, custom permission models, and policy enforcement that integrates with customers' existing identity and governance systems. Ship data protection features: Implement bring-your-own-key (BYOK) encryption, customer-managed keys, and data residency controls that give enterprises ownership over their most sensitive data. Develop infrastructure automation: Write Terraform modules and automation that enable reliable, repeatable enterprise deployments across reg

TypeScriptPythonGCPKubernetes
R
📍 Foster City, California, United States· Full-time
✓ Quality checkedCompany trend -85.9%

Replit is the agentic software creation platform that enables anyone to build applications using natural language. With millions of users worldwide, Replit is democratizing software development by removing traditional barriers to application creation. About the role: We are seeking talented distributed systems engineers who are passionate about building innovative solutions for application deployment. Your mission will be to enhance the capabilities of Replit Infrastructure, optimize performance across global regions, and drive efficiency while delivering an exceptional user experience. If you have a strong foundation in software development, a deep understanding of cloud technologies, and a track record of delivering high-quality code, we want to hear from you. In this role you will: Expand Replit's cloud infrastructure offerings: Launch new cloud products to be used by Replit Agent to build complex apps. Collaborate with cross-functional teams to design and implement these features, empowering developers with a comprehensive suite of tools to build and deploy their applications efficiently. Enhance reliability and scalability: Identify bottlenecks, optimize critical paths, and implement robust monitoring and alerting systems. Work closely with the SRE team to ensure high availability and minimal downtime. Enable our customers to seamlessly scale their applications to meet the demands of their growing user base. Improve utilization of cloud infrastructure: Analyze our infrastructure costs and identify opportunities for optimization. Implement strategies to reduce cloud expenses without compromising performance or reliability. This could involve techniques such as resource provisioning, auto-scaling, cost-aware scheduling, and data lifecycle management. Your efforts will directly contribute to the financial efficiency of our cloud services. Required skills and experience: Distributed systems: Track record of working with platform-as-a-service, distributed storage, o

GCPLinuxAIGo
SF
📍 United States· Full-time· Remote
✓ High-confidence listingCompany trend -100%

From $136K/yr

Quick readStrong listing-quality and freshness signals

About Stitch Fix, Inc. Stitch Fix (NASDAQ: SFIX) Stitch Fix is redefining retail by combining human creativity with advanced data science and Generative AI. As we build the future of personalized shopping, we’re equally committed to building yours. We believe in investing in our team as much as our technology. Join us to be a trendsetter in the industry and help us redefine what’s possible for our clients, while we help you reach your full potential. About the Role As an ML Platform Engineer at Stitch Fix, you will play a key role in building and maintaining the critical infrastructure that powers machine learning and AI across our organization. You will design, develop, and support scalable, resilient services and frameworks for ML model training and deployment, feature engineering and serving, candidate generation, AI agent deployment and observability, and other core platform capabilities. In this role, you'll contribute to the day-to-day operations of the ML Platform team, ensuring the smooth functioning of existing systems while driving improvements. You’ll collaborate closely with full-stack data scientists, offering consultation and support to help them unlock the full potential of our platform. With significant autonomy, you’ll have the opportunity to shape the future of ML and AI at Stitch Fix. Your ideas and expertise will drive improvements, codify best practices, and influence how we approach machine learning and AI systems at scale. Responsibilities: Collaborate with cross-functional teams, including data scientists, engineers, and business partners, to solve complex distributed systems and business challenges at scale. Be part of a team with high visibility across the organization, driving impactful solutions that make a difference. Share your ideas and help guide the team’s investments toward high-value opportunities. Foster a culture of technical collaboration and contribute to the development of scalable, resilient systems. About You You bring

PythonRedisAWSRest
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📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -80.2%

About the Team The Recursive Self-Improvement (RSI) team works across research, engineering, product, and infrastructure to build AI systems that accelerate and ultimately conduct high-quality research at OpenAI. We work to automate real research workflows and improve research productivity by building systems and feedback loops, designing evaluations, and training models to develop missing capabilities. Our work spans the full lifecycle of model training, evaluation, and deployment to help researchers move faster and tackle increasingly ambitious problems. About the Role We’re hiring research scientists , research engineers , and AI systems engineers to work on automating research at OpenAI. This role is based in San Francisco, CA. In this role, you will: Design evaluations for research judgment, hypothesis generation and testing, and long-horizon experiment execution. Turn real research workflows and model failures into data and evaluation flywheels. Improve model research capabilities through agent harnesses, synthetic data, RL environments, and model training. Build and maintain safe, reliable integrations between our models and OpenAI’s research infrastructure. Develop research agents, experiment-orchestration systems, and sandboxed runtimes that support real research workflows. Create metrics and economic models to understand RSI’s current and future effects on research productivity, model capabilities, and the safety of internal deployments. This is a high-ownership role for researchers and engineers who thrive in ambiguity, move fluidly between research and implementation, and turn emerging opportunities into rigorous, reliable, scalable results. You might thrive in this role if you: Have research or engineering experience across LLM training, model evaluations, agent systems, synthetic data, research infrastructure, or large-scale distributed systems. Are a strong generalist who can move between open-ended research and practical implementation, turning ambig

AWSRestAIGo
O
📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -80.2%

About the Team The compute infrastructure team runs the GPU fleet and large-scale compute clusters that serve the models backing ChatGPT and the API, while also supporting training workloads for our next generation models. We operate a large, modern GPU fleet and provide a unified platform for other OpenAI teams to seamlessly run production Applied AI and Research training workloads. 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 You’ll own the hands-on and automation work that brings WAN, fiber, carrier, and cloud-interconnect circuits into service. Partner with network engineers, fiber providers, cloud service providers, colocation teams, and data-center technicians to move each connection from ordered and patched to verified, stable, and ready for handoff. You’ll own Layer 1 troubleshooting and circuit bring-up while building workflows that translate reliable system or model output into precise, approved technician actions, capture field feedback, and drive each connection to a green-port handoff. The right person combines strong physical-networking judgment with practical automation skills: patch-panel and port mappings, optics and light levels, provider coordination, structured operational data, API or scripting workflows, and human-in-the-loop LLM tooling. Responsibilities Own Layer 1 activation and restoration for carrier circuits, dark fiber, wavelengths, Ethernet handoffs, and dedicated cloud interconnects across data centers and points of presence. Reconcile complete A-side/Z-side as-builts: circuit IDs, LOAs/CFAs, carrier demarcations, MMR/ODF/MDF and patch-panel positions, fiber pairs, cross-connects, optics, and device ports. Investigate no-light, low-light, wrong-port, link-flap, and error-rate issues across providers and CSPs; isolate continuity, dirty connectors, polarity, incorrect patching

AWSAzureRestAI
O
📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -80.2%

About the Team Our Cyber team builds AI systems and products that help trusted defenders understand and respond to cyber threats while improving the safety and reliability of frontier models in security-sensitive settings. The team works across product engineering, model training, evaluations, safeguards, and deployment to make advanced cyber capabilities useful to defenders and responsibly managed. We collaborate closely with Safety/Preparedness, Research, Security, Legal, Communications, GTM, and external partners across OpenAI’s broader cyber work. About the Role We’re looking for research and software engineers to join Codex Cyber. You’ll help define and ship security products, work with trusted defenders and customers, shape model training and access patterns, and build research and evaluation systems for assessing cyber capabilities, validating safeguards, and improving training data. This role is hands-on and cross-functional, connecting product launches, model development, safety work, and real-world security use cases. In this role, you will: Help define and execute the technical roadmap for Codex Cyber’s security products, including evaluations, safeguards, trusted-defender workflows, and deployment decisions. Work with trusted defenders, customers, and partner teams to understand cyber use cases, evaluate risk, and turn feedback into product and research priorities. Shape cyber-specific model training and access patterns, including data, evaluations, validation, and deployment criteria. Build and validate systems for measuring cyber capabilities, monitoring misuse risk, and proving safeguards work in practice. Collaborate with Safety/Preparedness, Research, Security, Legal, Communications, Go-to-Market, and external partners on company-wide cyber priorities. Translate frontier cyber research into launch-ready tools, operational playbooks, and durable infrastructure for Codex and security products. You might thrive in this role if you: Enjoy 0 -> 1 envi

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📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -80.2%

About the Team Codex is OpenAI's software engineering agent. Codex Security extends that work into one of the most important product areas in AI: helping organizations find, validate, prioritize, and fix real vulnerabilities in the software they build and depend on. The Codex Cyber team is building the product and platform foundations for AI-native application security. This includes Codex Security product experiences, cloud-based security analysis, platform controls across Codex, customer deployment and support tooling, and infrastructure that helps security researchers and cyber models improve over time. The team is early, small, and growing quickly, with a mandate to move fast and hire exceptional builders. About the Role We are looking for software engineers first: strong full-stack or product-minded generalists who can own ambiguous product and platform problems end to end. Security experience is helpful, and security curiosity is important, but this is not a role for security specialists who only occasionally write code. The right person is an excellent builder who is excited to work in security and can turn complex research, product, and customer needs into reliable systems. You will work across user-facing product surfaces, developer workflows, backend services, security analysis pipelines, cloud infrastructure, and internal tooling. You may build features that make Codex Security more useful for application security teams, systems that scale cloud-based security analysis, platform controls that make agentic coding safer, or infrastructure that helps security researchers and models become more effective. You will collaborate closely with engineering, product, security research, infrastructure, and customer-facing partners as Codex Cyber becomes a major product and platform investment for OpenAI. In this role, you will: Build end-to-end product features for Codex Security, from developer-facing interfaces to APIs, backend services, and workflow tooling. Own a

AWSRestAIGo
O
📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -80.2%

About the Team The Monetization team is a cross-functional group working across engineering, product, research, and design to build the foundational systems that will help OpenAI scale access to intelligence responsibly. Our mission is to develop user-first, privacy-preserving monetization products, including next-generation ads experiences that strengthen user trust, unlock economic opportunity, and support OpenAI’s long-term innovation. Monetization plays a critical role in enabling OpenAI to continue pushing the boundaries of AI capabilities while ensuring the benefits of AGI are broadly shared. We believe monetization must be aligned with user value, uphold rigorous privacy and safety standards, and sustain a healthy ecosystem of developers and businesses. This team operates in a greenfield environment and moves quickly through prototyping, experimentation, and iterative deployment. We partner closely with Product, Design, and Research to bring research breakthroughs into real-world systems at global scale. About the Role We’re looking for an experienced Software Engineer to build measurement systems that connect ad interactions to meaningful advertiser outcomes while protecting user privacy. In this foundational role, you’ll design infrastructure for conversion signals, attribution, reporting, and feedback loops across OpenAI’s ads products. This role is ideal for engineers who have built large-scale ads measurement, data, experimentation, marketplace, or distributed systems and want to apply that experience in a highly ambiguous 0→1 environment. You’ll work across event collection and normalization, deduplication and matching, attribution and modeled measurement, privacy-safe aggregation, reporting, and high-quality labels for ads optimization. We are hiring engineers who can independently own complex systems, make sound technical tradeoffs, and help define what should be built. You’ll work closely with Ads Delivery, Ads ML, Product, Research, Privacy, Data Sc

AWSRestAIGo
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📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -80.2%

About the Team OpenAI’s Infrastructure Operations team is responsible for the availability, reliability, and operational excellence of one of the world’s largest AI infrastructure networks. The team owns day-to-day operations of production AI networks across Industrial Compute's data centers, working with colocation providers, deployment teams, and hardware vendors to deliver highly available GPU infrastructure for AI training and inference workloads. About the Role We are seeking an Infrastructure Operations Engineer to operate and improve the large-scale Ethernet fabrics that support GPU clusters, storage systems, and management infrastructure. This role combines hands-on production operations with automation, observability, and incident response across a global AI network. The ideal candidate has experience operating high-availability data center, cloud, AI, or HPC networks and can move comfortably from physical-layer troubleshooting to routing and fabric behavior, change execution, and root-cause analysis. You will partner closely with network architecture, systems engineering, GPU engineering, storage engineering, security, deployment, site operations, service providers, colocation partners, and hardware vendors to raise reliability and reduce operational toil. Key Responsibilities Own the operational health, availability, and reliability of production AI network infrastructure across Industrial Compute's data centers. Monitor, troubleshoot, and resolve network incidents while meeting service-level objectives (SLOs), reducing Mean Time to Detect (MTTD), and minimizing Mean Time to Recovery (MTTR). Operate and maintain large-scale Ethernet fabrics supporting GPU compute, storage, and management networks. Execute production network changes, maintenance windows, and capacity expansions with minimal customer impact. Manage the hardware lifecycle, including switch and optics replacements, RMA coordination, software upgrades, and preventive maintenance. Support new A

PythonAWSAzureGit
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📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -80.2%

About the Team OpenAI's Industrial Compute organization is building the world's most advanced AI infrastructure ecosystem. Working alongside our cloud partners, infrastructure providers, and internal engineering teams, we operate hyperscale AI campuses that support the training and deployment of frontier AI models. The Site Operations team serves as OpenAI's on-site operational presence, helping ensure campuses operate safely, efficiently, and in alignment with Industrial Compute standards. We work closely with Hardware Operations, Infrastructure Delivery, Network Operations, Security, Facilities, Construction, and our infrastructure partners to support day-to-day site execution and maintain operational readiness. As Industrial Compute continues to expand globally, Site Operations plays a critical role in ensuring each campus is prepared to support reliable AI infrastructure at scale. About the Role We are seeking a Site Operations Technician to support the daily operation of Industrial Compute campuses. This role acts as OpenAI's on-site technical representative, helping coordinate activities across hardware operations, facilities, construction, logistics, security, and external service providers. You will perform routine site inspections, support asset tracking, coordinate vendor activities, assist with operational readiness, document site conditions, and help ensure infrastructure issues are identified and resolved quickly. The ideal candidate enjoys working in highly technical environments, is detail-oriented, and thrives in fast-paced operational settings where no two days are the same. Key Responsibilities Perform routine walkthroughs of Industrial Compute facilities to verify operational readiness and identify potential issues. Monitor site conditions and report abnormalities involving hardware spaces, network rooms, utilities, logistics areas, and common infrastructure. Support coordination of vendors, contractors, and partner organizations performing work o

AWSRestAIRust
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📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -80.2%

About the Team The Applied AI team safely brings OpenAI's technology to the world. We released ChatGPT, Plugins, DALL·E, and the APIs for GPT-4, GPT-3, embeddings, and fine-tuning. We also operate inference infrastructure at scale. There's a lot more on the immediate horizon. 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. We serve end-users directly through ChatGPT, and serve developers through our APIs, which power product features that were never before possible. About the Role The Engineering Acceleration team designs, builds and maintains the foundational systems that engineers use to build ChatGPT and the API. This is a fast-growing team and you will get a chance to own and define the strategy, vision, and plan for how to increase developer productivity. In this role, you will: Drive the design, development, and implementation of tools, systems, and processes that accelerate engineering velocity, reduce manual effort, and increase the quality of output. Use our latest AI tools to re-think how we can be the most productive team in the industry. Work closely with various teams within OpenAI to understand their workflows, challenges, and needs, and ensure the tools and systems built by the Engineering Acceleration team address these requirements. Bring new features and research capabilities to the world by partnering with product engineers to lay the necessary technical foundations. Guide and advise product engineering teams on best practices for ensuring observable, scalable systems. 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 of experience in engineering, including 3+ years of experience in infrastructure building tooling for developers. Have experi

PythonAWSKubernetesRest
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📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -80.2%

About the team The Applied team safely brings OpenAI's technology to the world. We released ChatGPT; Plugins; DALL·E; and the APIs for GPT-5, embeddings, and fine-tuning. We also operate inference infrastructure at scale. There's a lot more on the immediate horizon. Our customers build fast-growing businesses around our APIs, which power product features that were never before possible. ChatGPT is a prime example of what is currently possible. We simultaneously ensure that our powerful tools are used responsibly. Safe deployment is more important to us than unfettered growth. The Fraud Engineering team works within our Applied Engineering organization identifying and responding to fraudsters on our platform. We are looking for a software engineer with anti fraud & abuse experience to help architect and build our next-generation anti-fraud systems. About the role The Scaled Abuse team protects OpenAI’s products and customers by detecting, preventing, and responding to fraudulent and abusive behavior at scale. We build and operate the backend and data systems that power real-time detection, investigation workflows, and enforcement — balancing strong protections with a great user experience as the platform grows. Our work sits at the intersection of engineering and abuse expertise: we partner closely with Trust & Safety, Security, and Product to understand emerging attack patterns, translate messy signals into clear system behavior, and continuously harden our defenses. The problems are dynamic and ambiguous by default, so we value engineers who can quickly dive into an unfamiliar codebase, develop strong intuition about how it works end-to-end, and propose pragmatic improvements that make the entire stack more resilient. In this role, you will: Design and build systems for fraud detection and remediation while balancing fraud loss, cost of implementation, and customer experience Work closely with finance, security, product, research, and trust & safety ope

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