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Platform Infrastructure Engineer Jobs

10,000 active opportunities · Updated for October 2026

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

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3mo ago

About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career. About the team The Payments organization owns some of Stripe’s most critical payment flows and a platform that processes hundreds of billions of dollars in payments a year. Our team builds and scales the infrastructure and financial partner integrations that enables Stripe to accept, manage, and payout money across many countries, currencies, and payment methods. Our work is core to Stripe’s business, and thousands of developers use our platform and infrastructure to create valuable products and services that billions of people use. Our goal is to increase the GDP of the internet by making it easy to build global products, services, and platforms that handle money. Technical Operations roles in Payments are a dynamic and key component of Stripe's success. Focused on financial partner integrations and funds flow expansion, we sit at the intersection of product/platform engineers and financial partners, connecting them to ensure that everyone thrives and nothing is lost in translation. Our team partners closely with various finance and infrastructure engineering teams to ensure timely delivery of accurate data between financial partners, internal stakeholders, and Stripe leaders. We report and trace all of Stripe’s money movement transactions, including payments in more than 30 currencies and dozens of countries. You’ll own building and scaling Stripe’s manual and programmatic financial reporting and reconciliation processes for intra-company and outgoing money m

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About the Team OpenAI’s Platform and Infrastructure Engineering organization advances the mission of deploying artificial general intelligence (AGI) for the benefit of all by delivering secure, scalable, and resilient technology solutions. Our team builds and maintains robust infrastructure that safeguards OpenAI’s data and systems while ensuring employees are well-equipped and seamlessly connected. By prioritizing security, reliability, and user-centric solutions, we empower OpenAI employees to drive impactful AI research, corporate operations, and product innovation. About the Role As a Software Engineer: Internal Applications, Enterprise, you will build internal products that make technology support and administration safer, faster, and less dependent on manual intervention. You will help reduce reliance on broadly privileged human actions, turn recurring technology problems into paved paths, and build agentic systems that can help resolve tickets end to end. A core part of the role is building the interfaces that bring employees, AI agents, and human responders together in a shared ITSM experience, with the right context, controls, and handoffs at each step. We are seeking engineers who enjoy working across frontend and backend layers on ambiguous, high-leverage enterprise problems. You should bring strong product judgment, solid backend engineering fundamentals, and an interest in building software that changes how technology support, system administration, and agent-assisted operations are delivered. The best fit will care as much about the quality of the operator and employee experience as the correctness of the backend systems behind it. In this role, you will: Build frontend experiences that let employees request help, let agents gather context and take safe actions, and let human responders review, approve, or take over without losing the thread. Reduce reliance on broadly privileged manual actions by replacing them with narrow, auditable, policy-aware aut

awsrestai
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Ema (Enterprise Machine Assistant)
📍 San Francisco Bay Area• Full-time• $135K – $225K/yr
5mo ago

About Ema Ema is building the world’s leading Agentic AI platform to transform enterprise productivity. We enable organizations to delegate repetitive tasks to Ema, the Universal AI Employee, delivering 10x gains in workforce efficiency, across functions. Founded by former executives from Google, Coinbase, Flipkart, and Okta, our team includes engineers from premier tech companies and graduates of Stanford, MIT, UC Berkeley, CMU, and IITs. We are backed by industry leading investors including Accel, Naspers/Prosus, Section32, and angels like Sheryl Sandberg and Dustin Moskovitz. Headquartered in Silicon Valley and with offices in London, Bangalore and Vancouver, Ema is at the frontier of what Agentic AI can do in production — we ship real systems that run real business processes at scale. Who you are We are seeking an experienced DevOps Engineer to join our growing team and play a pivotal role in designing and building our platform and infrastructure as we continue to scale our product and user base. As a part of our team, you will be working in a dynamic, fast-paced environment to ensure the reliability, scalability, and performance of our systems, while focusing on service architecture and deployment, query optimization, distributed systems, data and machine learning infrastructure, and security and authentication. Most importantly, you are excited to be part of a mission-oriented, fast-paced, high-growth startup that can create a lasting impact. You will: Partner with product teams to architect, design, and build the foundational infrastructure for our products. Design, develop, and deploy highly available and scalable Multi-tenant SaaS solutions on any one of the public cloud networks like AWS, Azure and GCP. Leverage technologies such as Kubernetes, Helm, Terraform, and Istio to achieve infrastructure resilience. Drive the automation of infrastructure tasks, from provisioning to configuration management and deployment, utilizing tools like Terraform, Ansible, a

awsazuregcp
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D
11mo ago

P-78 At Databricks, we are passionate about enabling data and AI teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started. As part of the ML/AI Environments team you will build the system that enables the AI researchers and engineers to set up their desired training and serving environments. You’ll be joining a high-agency, high-visibility team operating at the frontier of AI infrastructure — with deep ties to research, product, and real-world enterprise use cases. Databricks Mosaic AI is one of our fastest-growing businesses helping thousands of our customers democratize AI within their organizations. We’re building the infrastructure that powers the next generation of AI. The impact you will have Build the infrastructure that enables ML and AI users to configure training and serving environments easily, reliably and reproducibly. Collaborate with other AI infrastructure teams to build the features that customers need to get more from the Databricks platform. Examples include improving performance of setting up virtual environments for short training and data processing sessions, improving observability to help customers debug when runs fail, etc. Interact with turnkey customers and product managers to envision new features and identify areas for improvement. Shape how developers and data scientists build and interact with AI on Databricks. What we look for 5+ years of experience in backend or infrastructure engineering wi

pythonjavaai
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D
Databricks
📍 Mountain View• $190K – $237.5K/yr
1mo ago

RDQ427R123 At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to tackle technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started. Databricks is looking for an Engineering Manager to lead the App Traffic team, responsible for critical networking infrastructure that powers communication across the Databricks platform. The team builds and operates Databricks’ unified service mesh, including ingress, service discovery, service-to-service communication, traffic management, and intelligent routing across AWS, Azure, and Google Cloud. These systems sit on the critical path of Databricks services and must deliver exceptional reliability, scalability, and performance while providing simple abstractions for application developers. As the Engineering Manager for App Traffic, you will lead a team of strong infrastructure engineers, shape the technical roadmap, and drive execution across complex, cross-functional initiatives. You will partner closely with senior engineers and infrastructure leaders on the architecture and evolution of Databricks’ traffic platform. The Impact You Will Have Lead, grow, and develop a high-performing team of engineers responsible for Databricks’ application traffic infrastructure. Drive the design and evolution of highly available distributed systems operating across multiple clouds and regions. Partner with senior and staff engineers on architectural decisions involving routing, control planes, reliability, scalability, and d

awsazureai
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D
Databricks
📍 San Francisco• $166K – $225K/yr
6mo ago

P-1428 At Databricks, we are passionate about enabling data and AI teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started. As part of the AI Platform team, you’ll build the substrate that powers everything from data apps, AI agents, model training, model serving, and vector search. You’ll be joining a high-agency, high-visibility team operating at the frontier of AI infrastructure — with deep ties to research, product, and real-world enterprise use cases. Databricks Mosaic AI is one of our fastest-growing businesses helping thousands of our customers democratize AI within their organizations. We’re building the infrastructure that powers the next generation of AI. We’re hiring across multiple teams in our AI Engineering org including: The impact you will have: Build infrastructure that powers our flagship offerings like MLflow, AI Gateway, Databricks Apps, Agent Framework, Agent Bricks, and Foundation Model APIs, to state a few. Improve reliability, latency, and efficiency of distributed AI workloads Collaborate with platform, infra, and ML teams to deliver seamless end-to-end experiences Shape how developers and data scientists build and interact with AI on Databricks What we look for: 5+ years of experience in backend or infrastructure engineering Strong programming skills in Scala, Go, or Python Experience with distributed systems, scalable APIs, or cloud-native infrastructure Familiarity with service

pythonazureai
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D
Databricks
📍 New York• $190K – $261.3K/yr
7mo ago

P-1592 At Databricks, we are passionate about enabling data and AI teams to solve the world's toughest problems, from making the next mode of transportation a reality to accelerating medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers, and customer obsessed, we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started. As part of the Unity AI Gateway team, you'll build the control plane that every AI request at Databricks passes through: partner and self-hosted models, agents, coding assistants, and MCP servers. It enforces budgets, routes each request to the right model, and applies guardrails inline. Unity AI Gateway is one of our fastest-growing businesses, moving trillions of tokens per week for thousands of customers. The impact you will have: Build the routing layer that picks the right model for each request across quality, cost, latency, availability, and remaining budget Improve reliability, latency, and efficiency of distributed AI workloads Collaborate with research, platform, infra, and AI/ML teams to deliver seamless end-to-end experiences Shape how developers and data scientists build and interact with AI on Databricks What we look for: 8+ years of experience in backend or infrastructure engineering Strong programming skills in Scala, or Go Experience with distributed systems, high-throughput APIs, or cloud-native infrastructure Familiarity with service-oriented architecture, deployment pipelines, and system observability Strong product and ownership mindset. You care about building the right solution, not just any solution Bonus points for: Experience with real-time serving, AI infrastructure, or GPU orchestration Exposure to platforms like

azureaiExcel
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D
Databricks
📍 New York• $165.3K – $219.7K/yr
9mo ago

P-1591 At Databricks, we are passionate about enabling data and AI teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started. As part of the AI Platform team, you’ll build the substrate that powers everything from data apps, AI agents, model training, model serving, and vector search. You’ll be joining a high-agency, high-visibility team operating at the frontier of AI infrastructure — with deep ties to research, product, and real-world enterprise use cases. Databricks Mosaic AI is one of our fastest-growing businesses helping thousands of our customers democratize AI within their organizations. We’re building the infrastructure that powers the next generation of AI. We’re hiring across multiple teams in our AI Engineering org including: The impact you will have: Build infrastructure that powers our flagship offerings like MLflow, AI Gateway, Databricks Apps, Agent Framework, Agent Bricks, and Foundation Model APIs, to state a few. Improve reliability, latency, and efficiency of distributed AI workloads Collaborate with platform, infra, and ML teams to deliver seamless end-to-end experiences Shape how developers and data scientists build and interact with AI on Databricks What we look for: 5+ years of experience in backend or infrastructure engineering Strong programming skills in Scala, Go, or Python Experience with distributed systems, scalable APIs, or cloud-native infrastructure Familiarity with service-oriented a

pythonazureai
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Location Details: Pune, India At GoDaddy the future of work looks different for each team. Some teams work in the office full-time; others have a hybrid arrangement (they work remotely some days and in the office some days) and some work entirely remotely.​ This is a hybrid position. You’ll divide your time between working remotely from your home and an office, so you should live within commuting distance. Hybrid teams may work in-office as much as a few times a week or as little as once a month or quarter, as decided by leadership. The hiring manager can share more about what hybrid work might look like for this team. Join our Team Our team builds and operates the foundational infrastructure platforms that power GoDaddy's engineering organization. We own critical services including secrets management, software distribution, host security controls, and live patching for thousands of Linux systems running on OpenStack. This role sits at the intersection of Linux engineering, platform engineering, reliability engineering, and security. You will help define how core infrastructure services are designed, operated, automated, and scaled across the enterprise! What you'll get to do... Design, build, and operate highly available, scalable, and secure infrastructure platforms supporting large-scale Linux environments, with a focus on reliability, resiliency, and operational efficiency Lead the architecture, implementation, and operation of infrastructure services, including OpenStack, enterprise secrets management, package management, software promotion pipelines, and platform lifecycle management Develop and maintain automation solutions using infrastructure-as-code, Ansible, Python, Go, and self-service capabilities to improve efficiency and reduce operational overhead Build and improve observability and reliability practices through monitoring, logging, alerting, dashboards, managing incidents, analyzing underlying causes, disaster recovery, and service health reporting

pythongitlinux
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SpaceX was founded under the belief that a future where humanity is out exploring the stars is fundamentally more exciting than one where we are not. Today, SpaceX is actively developing the technologies to make this possible, with the ultimate goal of making life multiplanetary and expanding consciousness to the stars. SpaceXSI is building Super Intelligence to help humanity understand the universe. Our teams are building the full Super Intelligence stack: from our Colossus supercomputers, to Grok models, to our suite of applications, including Grok Bot, Grok Build, Grok Imagine, Grok Voice, and X. We're creating a powerful flywheel where more compute trains better models, better models power more useful products, and what we learn from people using those products shapes what we build next. RESPONSIBILITIES: Design, build, and implement a large-scale distributed system that powers one of the world's largest supercomputing clusters. Dive into the low-level stack to profile, debug, and optimize performance across diverse systems, including GPUs, Linux kernel, networking, and filesystems, to achieve peak efficiency. Collaborate on hardware, software, and algorithm co-design to push the boundaries of AI training. Maintain and innovate on our codebase to ensure scalability and reliability. Develop tools to enhance team productivity and streamline workflows. BASIC QUALIFICATIONS: Systems programming experience in C, C++, or Rust Computer systems fundamentals with a grasp of how computers execute code from transistors to high-level applications. Hands-on expertise with Kubernetes (K8s), including cluster architecture, pod lifecycle, networking (CNI), storage (CSI), service mesh, and production-grade operations PREFERRED SKILLS AND EXPERIENCE: Collaborate in a fast-paced, open environment to design and foundational systems. Strong debugging skills across the full stack — from kernel and OS up through container orchestration layers Deep knowledge of operating systems intern

dockerkuberneteslinux
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ReqID: FEQ427R149 Location: London Skills: Networking, Security, Platform, DevOps, Databricks, Cloud - AWS, GCP, Azure, Infrastructure - First preference would be GCP experience Recruiter: Dina Hussain As an Infrastructure & Platform Specialist Solutions Engineer, you will serve as a trusted technical advisor, helping enterprise customers with the architecture, administration, and security of their Databricks deployments on their cloud of choice (AWS, Azure, or GCP). You combine solid technical expertise with a growing ability to connect architecture decisions to customer outcomes. The Impact You Will Have Guide enterprise customers through the full lifecycle of Databricks on their cloud platform, including platform administration from initial architectural design to production deployment Architect secure, scalable enterprise deployments that satisfy complex cloud networking (virtual networks, private connectivity), identity (cloud IAM and enterprise identity providers), and security compliance standards Act as a technical specialist in core areas such as cloud infrastructure, infrastructure-as-code (IaC), cloud networking, and identity management Support technical wins in competitive scenarios by demonstrating Databricks' differentiation through custom-built solutions Collaborate with cross-functional resources (DSAs, SAs, FDE, Partners) to contribute to solutions for complex customer needs Operate with growing autonomy on well-scoped engagements, with guidance from senior architects on the most complex designs Influence product direction by providing structured feedback on customer requirements and competitive gaps What We Look For 4+ years in solutions architecture, technical pre-sales, or a Network architecture hands-on technical role Strong expertise across the following areas: Security & Identity: Cloud security controls, platform/network/data security, encryption, vulnerability management, compliance, and identity protocols. This includes cloud-

pythonawsazure
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A
Anyscale
📍 San Francisco• Full-time• Remote• $215K – $265K/yr
28 days ago

About Anyscale: At Anyscale , we're on a mission to democratize distributed computing and make it accessible to software developers of all skill levels. We’re commercializing Ray , a popular open-source project that's creating an ecosystem of libraries for scalable machine learning. Companies like OpenAI , Uber , Spotify , Instacart , Cruise , and many more, have Ray in their tech stacks to accelerate the progress of AI applications out into the real world. With Anyscale, we’re building the best place to run Ray, so that any developer or data scientist can scale an ML application from their laptop to the cluster without needing to be a distributed systems expert. Proud to be backed by Andreessen Horowitz, NEA, and Addition with $250+ million raised to date. About the Role Anyscale is seeking a Staff Software Engineer to lead the technical vision for our Infrastructure team. As a Staff Engineer, you will be responsible for the architectural evolution of our control plane and data plane, ensuring that our "infinite laptop" vision scales to meet the most demanding distributed AI workloads in the world. You will act as a force multiplier, setting the standards for Kubernetes-based cloud-native infrastructure while mentoring engineers and driving cross-functional alignment across the Ray open-source community and our proprietary product teams. Key Responsibilities Architectural Leadership: Define and drive the multi-year technical roadmap for services that orchestrate Ray clusters across diverse cloud and on-premises environments. Systemic Optimization: Lead the design and optimization of high-performance control plane components specifically tailored for large-scale, heterogeneous AI/ML workloads. Platform Reliability: Establish the organization-wide standards for the reliability, scalability, and observability of Anyscale-managed infrastructure. Strategic Integration: Direct the long-term strategy for accelerator integration (GPUs, TPUs) and container management to ens

REMOTEpythonawsazure
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Okta
📍 Bellevue, Washington• Full-time• $232K – $319K/yr
12mo 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 Infrastructure Platform and Shared Services Team Okta authenticates, authorizes and provisions millions of users a day. The service is hosted on Amazon Web Services (AWS) across multiple availability zones and geographically separated regions. The service is designed for high throughput and 99.999 availability. We're looking for a technical leader to help us continue to scale the service with great people and reliable, cost-effective, and efficient infrastructure, processes, and tooling. As the Sr. Manager of Infrastructure Platform and Shared Services, you will oversee multiple teams focused on Edge networking, K8s platform, Observability, automation platform & tooling. What you’ll be doing Lead the Infra platform and shared services org and various initiatives across SRE & Infrastructure organization. Build a world-class observability platform and monitoring capabilities enabled with self-service Accelerate the velocity of SRE and product engineering by developing robust platforms, powerful tooling, and intuitive self-service capabilities. Own the design and operation of scalable, self-service Cloud infrastructure platforms (e.g. Observability Platform, SRE Productivity, deployments, and Edge Infrastructure) Lead, mentor, and grow a high-performing team of engineers and managers across SRE and infrastructure shared services domains. Perform engineering design evaluations and ensure the completion of projects within resource,

awskubernetesmachine learning
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Clickup
📍 United States• Full-time• Remote• $250K – $300K/yr
3mo ago

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. 🚀 This role bridges infrastructure and product engineering: you'll build genuine partnerships across product, AI, and enterprise teams so that ownership is shared and velocity is never blocked by platform constraints. As a leader, you'll set a forward-looking cloud vision, proactively align with stakeholders across the business, and ensure the platform scales for multi-shard, multi-region growth while meeting security and compliance commitments (SOC 2, business continuity/disaster recovery, and enterprise security frameworks). You'll implement and drive the adoption of AI-powered tooling and autonomous agents within the infrastructure organization. The Role: Cost Efficiency: Deliver measurable annual infrastructure savings by executing the migration of data workloads to EKS and self-hosting key services. Ingress Convergence: Deprecate legacy frontend ALBs and consolidate to a single EKS-managed ALB per shard, unblocking faster deployments across the org. Coverage & Bench Depth: Eliminate single points of ownership across Networking, OpenSearch, and Terraform through cross-training and targeted hiring. Stakeholder Alignment: Stand up a recurring alignment cadence with Product, AI, Enterprise, and Security so infra planning is driven by demand, not ad-hoc interrupts. Automation: Ship automated shard buildout via Backstage to remove manual toil from enterprise scaling. Reliability: Cut P0/P1 incidents attributed to Cloud Platform (DNS, ALB misconfiguration, EKS) through hardened ingress patterns and Terraform-policy guardrails. Own incident response and RCA follow-through for the team. Roadmap Ownership

REMOTEawsmachine learningartificial intelligence
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HI
HP IQ
📍 United States• $150K – $220K/yr
26 days ago

Who We Are HP IQ is HP’s new AI innovation lab. Combining startup agility with HP’s global scale, we’re building intelligent technologies that redefine how the world works, creates, and collaborates. We’re assembling a diverse, world-class team—engineers, designers, researchers, and product minds—focused on creating an intelligent ecosystem across HP’s portfolio. Together, we’re developing intuitive, adaptive solutions that spark creativity, boost productivity, and make collaboration seamless. We create breakthrough solutions that make complex tasks feel effortless, teamwork more natural, and ideas more impactful—always with a human-centric mindset. By embedding AI advancements into every HP product and service, we’re expanding what’s possible for individuals, organisations, and the future of work. Join us as we reinvent work, so people everywhere can do their best work. About The Role As a Senior Platform Engineer at HP IQ, you will help build and evolve the infrastructure, tooling, and shared platform capabilities that enable our engineering teams to develop and operate reliable, secure, and scalable services across cloud and edge environments . You will work closely with application, services, AI/ML, and security teams to improve developer velocity, production readiness, reliability, and operational efficiency across a heterogeneous infrastructure footprint. What You Might Do Design, build, and maintain shared infrastructure and platform capabilities across cloud and edge environments. Build automation and self-service tooling that improves engineering velocity and operational consistency. Develop and maintain Infrastructure-as-Code, deployment workflows, and environment provisioning. Partner with engineering teams on production readiness, including reliability, security, observability, scalability, and recovery. Improve monitoring, alerting, incident response, and operational tooling across distributed environments. Automate repetitive operational t

pythonkubernetesai
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