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Staff Platform Infrastructure Engineer Jobs

7,423 active opportunities · Updated for October 2026

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Explore current staff platform infrastructure engineer jobs. Use filters to narrow by work mode, employment type, experience and date posted.

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Cohere
📍 San Francisco• Full-time• Remote• $190K – $325K/yr
9mo ago

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why this role? Are you energized by building high-performance, scalable and reliable machine learning systems? Do you want to help define and build the next generation of AI platforms powering advanced NLP applications? We are looking for Members of Technical Staff to join the Model Serving team at Cohere. The team is responsible for developing, deploying, and operating the AI platform delivering Cohere's large language models through easy to use API endpoints. In this role, you will work closely with many teams to deploy optimized NLP models to production in low latency, high throughput, and high availability environments. You will also get the opportunity to interface with customers and create customized deployments to meet their specific needs. You may be a good fit if you have: 5+ years of engineering experience running production infrastructure at a large scale Experience designing large, highly available distributed systems with Kubernetes, and GPU workloads on those clusters Experience with Kubernetes dev and production coding and support Experience with GCP, Azure, AWS, OCI, multi-cloud on-prem / hybrid serving Experienc

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Reddit
📍 United States• Remote• $292.5K – $409.5K/yr
1mo ago

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . About the Role: We are seeking a Senior Staff Machine Learning Engineer to define and accelerate how we leverage agentic AI to transform machine learning models and modeling workflows. This high-impact role focuses directly on modeling leverage —enhancing model quality and velocity—rather than building general infrastructure. As a senior staff engineer, you will operate as a technical leader across the entire modeling loop, utilizing modern AI-assisted development systems (such as Claude, Cursor, and comparable tools) to make model development faster, more rigorous, and significantly more effective across the organization. Why Join Us? This role offers a domain-flexible platform to redefine how ML engineering is done. If you are passionate about combining deep ML fundamentals with the vanguard of agentic AI to multiply team impact, we’d love to talk to you. What you’ll do: Develop advanced ML models and the agentic workflows that help teams design, train, evaluate, and improve them. Use tools such as Claude, Cursor, and comparable AI-assisted development systems to investigate model behavior, generate and test hypotheses, automate repetitive analysis, and improve code and experiments. Build reliable loops for data and label analysis, feature and embedding development, architecture comparison, hyperparameter optimization, error analysis, and experiment readouts. Design evaluation harnesses that measure both model outcomes and agent/workflow quality, including correctness, reproducibility, regressions, cost, a

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Nuro
📍 United States• Full-time• From $193.9K/yr
2mo ago

Who We Are Nuro believes self-driving vehicles are the most immediate and profound opportunity for AI to drive positive change in the physical world. Safer streets, more time for what matters, and easier access to the world around us, that’s why we’re building a universal autonomy platform: self-driving for all roads and all rides. Founded in 2016, Nuro is a physical AI company developing Level 4 autonomous driving technology for a wide range of vehicles, use cases, and markets. Powered by the Nuro Driver™, our universal autonomy platform enables the global mobility ecosystem to deploy autonomy at scale, from robotaxis and logistics fleets to personal vehicles. With years of real-world deployment experience and a flexible, partner-led business model, Nuro is working toward a future where millions of autonomous vehicles powered by our technology help make everyday life safer, easier, and more connected. Nuro has raised over $2B in capital from Uber, NVIDIA, Google, Softbank, Fidelity, T. Rowe Price, and other leading investors. About the Role The ML Infrastructure team is responsible for building & improving the core infrastructure for autonomy teams at Nuro. In this role, you will work closely with teams across Nuro, to design, build and deploy core infrastructure components in machine learning model life cycle, to push the autonomous future forward. You will have an opportunity to work across the full stack of machine learning solutions - from designing robust and scalable model & data pipelines to building to deploying the optimized models on Nuro’s fleet of self-driving robots! About the Work Design and develop ML workflow pipelines to train, optimize, validate, and deploy Nuro autonomy models. Develop and maintain continuous testing and monitoring systems for core ML infrastructure components. Develop observability to track ML model lifecycles from data generation to on-road validation. Maintain an in-house ML inference platform to serv

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Reddit
📍 United States• Remote• $292.5K – $409.5K/yr
6mo ago

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Who We Are: The Machine Learning Platform team at Reddit is a high-impact team that owns the infrastructure that powers recommendations, content discovery, user and content quantification, while directly impacting other teams such as Growth, Ads, Feeds, and Core Machine Learning teams. What You’ll Do: As a Senior Staff Software Engineer, you will help define and lead the vision for Reddit’s large-scale GenAI Platform, shaping the strategy, architecture, and operating model that enable teams across the company to build, deploy, and scale generative AI products with confidence. Contribute to the design, implementation, and maintenance of the LLM Gateway, focusing on features like unified API endpoints for internal/externally hosted LLM, rate/token limit management, and intelligent failover mechanisms to boost uptime and reliability. Lead and execute the vision, strategy, and roadmap for Reddit’s large-scale GenAI Platform. Define the platform architecture and operating model that enable teams to build, deploy, and scale GenAI products reliably. Drive the strategy for a unified LAG Gateway supporting internally and externally hosted LLMs through consistent APIs and abstractions. Set the direction for core platform capabilities such as rate and token limit management, intelligent failover, and production resilience. Shape Reddit’s approach to an enterprise-grade RAG system Establish the strategic direction for agentic AI workflows and tool-use patterns across the platform. Own the end-to-end platform strategy from concept t

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Who We Are Verkada is transforming how organizations protect their people and places with an integrated, privacy-sensitive AI-powered platform that includes solutions for video security, access control, air quality sensors, alarms, intercoms, and visitor management. We’ve got serious momentum in the market: more than 30,000 customers (including 100+ of the Fortune 500), a $5.8B valuation , more than $1 billion in annualized bookings, and backing from CapitalG, Sequoia Capital, General Catalyst, Felicis Ventures, Next47 and more. Physical AI is one of the most consequential technology shifts of our time, and Verkada is at the center of it. You can look at all kinds of communities to see our platform’s impact in the world. It's the retailer that uses our agentic AI to deter theft before it happens. The warehouse that uses AI-powered alerts to make sure its team is protected on the floor with proper PPE. The school that’s alerted to a threat in real-time and triggers a lockdown in seconds, not minutes. We’re rapidly scaling this impact: today, more than 2 million Verkada devices are deployed across 170+ countries. About the Role As a Staff Software Engineer on the team, you will shape Verkada's internal access management architecture, define technical strategy, and build the infrastructure used to provision, review, and audit access across the company. From evolving our in-house access platform to setting guardrails for AI-driven and agentic workflows, your technical leadership will directly impact every team at Verkada. What You'll Do Own the technical architecture of Verkada's internal access management platform, the system of record for employee, service, and non-human access across company resources. Design, build, and operate highly available, observable backend infrastructure for access provisioning and review, using modern backend languages and cloud-native tooling. Extend and harden integrations with identity providers (e.g. Okta) — custom roles, en

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21 days ago

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . Sr. Staff Software Engineer, Product ML Infrastructure Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Pinterest’s Product ML Infrastructure (PMLI) team enables fast, safe, and efficient delivery of AI/ML solutions across Ads and Core critical products. We build unified data,

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Perplexity
📍 San Francisco• Full-time• $220K – $405K/yr
1mo ago

About Perplexity AI In 2026, we launched Computer, the defining product for the new era of agentic AI. We’ve scaled beyond the millions of people using Perplexity every day for research, shopping, investing and curiosity into a new paradigm of using AI to transform knowledge into action. As an engineer at Perplexity, your role will be to build products and systems that define how AI empowers humans to think, decide and act. You’ll ship fast and work between both product and infrastructure advancements in our technology. Why Perplexity is different Craftsmanship . We build high quality, tasteful products targeting both the AI native and AI curious. Ownership . You identify the problem, design the solution and ship it. Entrepreneurship . We think like founders, act with urgency, and hustle to deliver for each other and our users. Scholarship . Work among highly talented peers, pursuing knowledge and truth, upleveling ourselves, our teams, and our products. Partnership . We amplify each others' strengths, break down silos, and give selflessly to help our colleagues deliver excellence. About the Role Perplexity is looking for a deeply technical software engineer to own and evolve our model serving platform, which is responsible for connecting our products and research systems with our inference layers. This mission-critical system gives teams one fast, reliable interface across providers. You will work at the intersection of distributed systems, AI products, and infrastructure. You will make it dramatically easier for teams across Perplexity to adopt new models, run rigorous experiments, and ship dependable products. The ideal candidate combines sound technical judgment forged in production systems with active curiosity around the rapidly changing capabilities and failure modes of frontier models. You will design core abstractions, lead high-conviction technical decisions, and write production Rust and Python for a service that serves hundreds of millions of model reque

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We are hiring an experienced Security Software Engineer (Staff or Senior) for our Infrastructure Security team to design and build scalable security controls and services within MongoDB Atlas multi-cloud infrastructure. The team sits within the Site Reliability Engineering organization and works with other engineering teams to ensure that our infrastructure adheres to the highest security standards. This role can be based out of our Dublin office, or work fully remotely in Ireland. Responsibilities: Design and build core security primitives and services that protect MongoDB Atlas compute, networking, and identity across AWS, Azure, and GCP Build secure-by-default infrastructure using Linux security mechanisms (AppArmor, SELinux, seccomp, cgroups), Kubernetes, and eBPF to enforce runtime policies and gain deep visibility into systems behaviour Develop APIs, automation, and tooling that manage security posture at scale (CSPM, vulnerability management, workload identity) and provide monitoring, logging, and alerting pipelines that integrate with our tooling (Grafana, Splunk, Victoria Metrics.) Integrate security into our CI/CD and infrastructure-as-code workflows (Terraform) so that security controls are versioned, reviewed, and deployed just like any other code Lead complex projects end‑to‑end, from problem discovery and design docs to implementation, rollout, and long‑term ownership Collaborate with SRE, platform and product engineering teams to define secure architectures for new infrastructure and services Qualifications: You might be a great fit if you match some of the following: 5+ years of experience in Software Engineering, Site Reliability Engineering, or similar roles, preferably with relevant security work Proficiency with at least one programming language (Java, Golang, Rust, Python, or C/C++) and experience with infrastructure-as-code tools (Terraform) to automate security configurations and processes A deep understanding of Linux and networking concepts,

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We are hiring an experienced Security Software Engineer (Staff or Senior) for our Infrastructure Security team to design and build scalable security controls and services within MongoDB Atlas multi-cloud infrastructure. The team sits within the Site Reliability Engineering organization and works with other engineering teams to ensure that our infrastructure adheres to the highest security standards. This role can be based out of our New York City, Austin, Seattle or San Francisco offices, or work fully remotely on standard East Coast business hours. Responsibilities: Design and build core security primitives and services that protect MongoDB Atlas compute, networking, and identity across AWS, Azure, and GCP Build secure-by-default infrastructure using Linux security mechanisms (AppArmor, SELinux, seccomp, cgroups), Kubernetes, and eBPF to enforce runtime policies and gain deep visibility into systems behaviour Develop APIs, automation, and tooling that manage security posture at scale (CSPM, vulnerability management, workload identity) and provide monitoring, logging, and alerting pipelines that integrate with our tooling (Grafana, Splunk, Victoria Metrics.) Integrate security into our CI/CD and infrastructure-as-code workflows (Terraform) so that security controls are versioned, reviewed, and deployed just like any other code Lead complex projects end‑to‑end, from problem discovery and design docs to implementation, rollout, and long‑term ownership Collaborate with SRE, platform and product engineering teams to define secure architectures for new infrastructure and services Qualifications: You might be a great fit if you match some of the following: 5+ years of experience in Software Engineering, Site Reliability Engineering, or similar roles, preferably with relevant security work Proficiency with at least one programming language (Java, Golang, Rust, Python, or C/C++) and experience with infrastructure-as-code tools (Terraform) to automate security configurations

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Pinterest
📍 Palo Alto• Remote• $208.6K – $429.5K/yr
15 days ago

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . The AI Platform team delivers essential tools and infrastructure utilized by hundreds of AI and ML engineers across Pinterest, powering crucial functions such as recommendations, ads, visual search, growth/notifications, and trust and safety. Our primary objectives are to ensure AI and ML systems maintain production-grade quality and enable rapid iteration for our customers. As a Senior Staff Software Engineer on the AI Platform team, you will shape and scale Pinterest’s AI/ML evaluation platform into a unified, reliable system adopted company-wide. You will identify modernization opportunities, elevate the roadmap, and execute technical strategy of a durable evaluation system for GenAI and ML workloads at Pinterest, partnering across engineering, research, product, and safety to improve quality, launch decisions, and trust in AI-powered experie

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Pinterest
📍 United States• Full-time• Remote• $208.6K – $429.5K/yr
6mo ago

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . The Data Product Platform is mission-critical to accelerating data-driven decision-making at Pinterest on the foundation of 100s of thousands of tables and an exadata-scale data warehouse. We strive to provide effortless, efficient, and reliable data products and platforms that power the entire company. We achieve this by investing in three core areas: Data Warehouse: Building and managing the foundational data warehouses that enable key analyses across both our core engagement and monetization products. Analytical Velocity: Creating powerful analytical tools that empower internal data users to leverage our vast data assets and capable infrastructure effectively. Data Governance: Defining and implementing the data governance policies and tools necessary to ensure the responsible, efficient and compliant storage and handling of all data. We are s

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Zscaler (NASDAQ: ZS) accelerates digital transformation so customers can be more agile, efficient, resilient, and secure. The Zscaler Zero Trust Exchange platform protects thousands of customers from cyberattacks and data loss by securely connecting users, devices, and applications in any location. Distributed across 200+ public data centers globally and thousands of private sites at the edge, the SASE-based Zero Trust Exchange is the world’s largest in-line cloud security platform. We believe the future of work is Human + AI and are building an AI-native enterprise where human potential is amplified by machine intelligence to solve the world’s hardest security challenges. Driven by deep customer obsession, we are committed to the mission, outcome, and to each other. We bring these commitments to life through three core behaviors: ownership and collaboration, trust through outcomes and impact, and a challenge culture with ongoing feedback. Ready to make an impact at the company pioneering security transformation in the AI era? Join us at Zscaler. Role We are seeking an experienced Staff Site Reliability Engineer to join our dynamic SRE Cloud Infrastructure & Operations team. In this high-impact role, you will report directly to the Director of Site Reliability Engineering and play a pivotal part in architecting, scaling, and maintaining our next-generation cloud infrastructure. You will bridge the gap between development and operations, ensuring our large-scale distributed systems are highly available, secure, and incredibly resilient. What You'll Do (Key Responsibilities) Architecting & Automating: Design, implement, and manage various advanced cloud management automations to eliminate toil and accelerate delivery Container Orchestration: Oversee and optimize containerized architectures using EKS and GKE to ensure robust production performance Observability Systems: Lead the creation, deployment, and optimization of highly scalable monitoring and alerting s

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Okta
📍 Maryland• Full-time• $174K – $238K/yr
2mo ago

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. The Federal SRE Team We are looking for an experienced Staff Site Reliability Engineer to join Okta's Federal SRE team for the Emerging Products Group (EPG). Our mission is to build highly reliable, scalable, and secure cloud services that our customers can trust. We embrace an automation-first mindset and continuously invest in platform engineering, observability, and operational excellence to enable our engineering teams to move quickly and safely. The Staff SRE, Classified Opportunity This role is ideal for an engineer who enjoys solving complex technical challenges at scale, building automation, and improving the reliability of production systems. You will serve as a technical leader within the EPG SRE organization, partnering closely with software engineers, architects, and product teams to design, build, and operate world-class cloud services. The ideal candidate exemplifies the philosophy of "if you have to do it more than once, automate it" and possesses a strong passion for continuous improvement, operational excellence, and software engineering. Security Clearance: Active U.S. TS/SCI clearance with Full Scope Poly Compliance Expertise: Proven experience navigating Federal and DoD compliance frameworks, specifically FedRAMP and Impact Level 6 (IL6) What you’ll be doing: Reliability & Operations Design, build, and operate large-scale cloud infrastructure and production services. Participate in an on-call rotation supporting hi

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4mo ago

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. What You’ll Be Doing Design, build, and operate highly scalable, reliable, and secure infrastructure powering our production systems across AWS and GCP. Lead major reliability and modernization initiatives, including container platform migrations (e.g., ECS to EKS/GKE) and microservice enablement across multi-cloud environments. Serve as a technical authority in Kubernetes (EKS and GKE), cloud infrastructure (AWS and GCP), and modern CI/CD practices (GitOps, automation pipelines). Partner with development teams to architect and enable microservice-based applications, ensuring production readiness, scalability, and observability. Implement and manage infrastructure as code (Terraform, Ansible) to automate provisioning, scaling, and configuration management across multiple cloud providers. Drive improvements in observability, performance, and cost efficiency through robust monitoring, logging, and alerting systems that span AWS and GCP. Champion SRE best practices — defining SLOs/SLIs, conducting blameless postmortems, and continuously improving incident response. Lead complex technical projects from conception to completion, managing timelines, and technical dependencies across teams. Mentor engineers across teams, fostering a culture of reliability, automation, and continuous learning. Collaborate with security and compliance partners to ensure infrastructure adheres to best practices and standards (e.g., IAM Federation, Workload Identity). Participate in t

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5mo ago

About the job Build the cloud platform that turns Graphcore AI systems into usable, scalable services. Graphcore needs a Bristol-based Staff Cloud Engineer to develop and deploy private and public cloud services for AI compute. You will join the Cloud Platform team within Software Platform, close to datacentre operations and product development. Your work will shape how internal users and customers access large-scale AI systems. You will keep critical infrastructure available while helping pre-release hardware and software become reliable cloud services. You will operate and extend OpenStack-based services, automate deployment with infrastructure-as-code, and improve observability across the fleet. You will benchmark, validate and optimise systems spanning Graphcore hardware, servers, switches and storage. This role suits someone who wants ownership of hard infrastructure problems, not a narrow ticket queue. Expect unproven components, direct user feedback, and decisions that move quickly into production. The team and culture The Cloud Platform team turns Graphcore products into large-scale AI solutions for internal users and customers. Work happens close to the systems, with engineers deploying, measuring and improving services directly. You will work with Software Platform, Datacentre Operations, Product Development, Engineering and QA. The team values people who take responsibility for unclear problems and make progress without waiting for perfect inputs. The team makes decisions from evidence: metrics, benchmarks, user impact and system behaviour. Engineers speak up, surface risks early and own corrective actions when systems need attention. What we’re looking for A relevant degree or equivalent practical experience, with proven ability to scope and deliver technical infrastructure work. Experience operating on-premises or private-cloud environments, with strong ownership of end-user availability. Strong Linux system administration and scripting sk

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