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Staff Machine Learning Scientist Jobs

3,415 active opportunities · Updated for October 2026

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Explore current staff machine learning scientist jobs. Use filters to narrow by work mode, employment type, experience and date posted.

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Okta
📍 Bengaluru• Full-time
1mo 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. Principal Software Engineer - PAM Okta is the identity standard. The Okta Identity Cloud is an independent and neutral platform that securely connects the right people to the right technologies at the right time. We help organizations do two things - secure and manage their extended enterprise, and transform their customers' experiences. With over 14,000 customers, 7000+ app integrations, and well over 200 million registered users, we are only getting started. The Okta Privileged Access Management (PAM) is an identity-centric approach to a common and critical privileged access use case. Our elegant Zero Trust architecture is purpose-built for the modern cloud and helps customers solve challenging security and operations pain points at scale. We're looking for a staff-level fullstack engineer to join a team of highly skilled and talented team players who're proud of what they own and deliver. Our elite team is fast, creative, and flexible; with a weekly release cycle and individual ownership, we expect great things from our engineers and reward them with stimulating new projects, new technologies, and the chance to have significant equity in a company that is changing the cloud computing landscape forever. You Will Leverage cutting-edge AI pair-programmers and LLMs (such as Copilot and Claude) to accelerate the development of secure, enterprise-grade Privileged Access Management (PAM) products. Proven expertise leveraging AI devel

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DC
21 days ago

Role Overview Build reliable software services that power products, platforms, and business decisions. As a Senior Software Developer, you’ll design and deliver scalable applications, backend services, and integrations that perform well in production and evolve with changing business needs. You’ll apply strong software engineering practices across APIs, data-intensive applications, cloud services, AI-enabled solutions, and deployment pipelines. You’ll help shape technical solutions, improve system reliability, and contribute to a high-quality engineering culture. Here’s a breakdown of what you’ll do (not all of it, just the important stuff) Design and develop scalable backend services and applications using Python or TypeScript. Lead the development of APIs, integrations, reusable software components, and AI-enabled features. Build reliable solutions for data ingestion, manipulation, service-to-service communication, and intelligent automation. Apply AI technologies and modern software engineering practices to improve product capabilities, developer productivity, and operational efficiency. Make sound technical decisions around architecture, performance, security, scalability, and maintainability. Deploy and operate applications using AWS services and CI/CD practices while improving testing, monitoring, documentation, and delivery standards. These are the essentials you’ll need to get an interview 5+ years of professional experience developing and delivering production software. Strong hands-on experience with Python; TypeScript or similar languages is also valuable. Proven experience building backend services, APIs, integrations, and service-oriented applications. Experience applying AI technologies, such as generative AI, machine learning services, intelligent automation, or AI-enabled application features. Strong understanding of software design principles, testing, debugging, performance optimization, and secure development. Experience working with cloud platfor

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DC
Diligent Corporation
📍 Vancouver• Full-time• From C$131K/yr
21 days ago

You love turning real business problems into working AI solutions — and you’re not afraid to roll up your sleeves to ship them. In this role, you’ll lead Diligent’s internal AI Solutions function , a small, high-impact team that is embedding AI and GenA I into the systems thousands of colleagues use every day across Marketing, Sales, Customer Success, Finance, HR, Legal, and Product & Engineering. You’ll set the AI vision and roadmap for internal tools, architect solutions, and still build hands-on — from prototypes and reference implementations through to production-grade integrations . You’ll own how AI shows up inside ERP, CRM, BI and core IT platforms, and you’ll be accountable for making those solutions reliable, secure, compliant, and measurably valuable for the business. If you enjoy being a “player-coach” who can move seamlessly between executive conversations and deep technical reviews, this role gives you the scope, visibility, and impact to shape how a global SaaS leader uses AI to run smarter and faster. Here’s a breakdown of what you’ll do (not all of it, just the important stuff) Lead, coach, and grow a high-performing team of AI Solutions Architects and Engineers, setting clear goals and building the capabilities the business needs as AI demand scales. Define and own the strategy, vision, and roadmap for internal AI solutions, translating business priorities into a focused portfolio of AI and platform initiatives. Design and deliver end-to-end AI/GenAI solutions — from ideation and prototyping through production deployment, monitoring, and continuous improvement. Embed AI capabilities (such as RAG, copilots, agents, summarization, and classification) into core business applications including ERP, CRM, BI, and other enterprise systems in a robust, maintainable way. &nbsp

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SpaceXAI
📍 London• Full-time• £107K – £262K/yr
21 days ago

SpaceXAI’s mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge. Our team is small, highly motivated, and focused on engineering excellence. This organization is for individuals who appreciate challenging themselves and thrive on curiosity. We operate with a flat organizational structure. All employees are expected to be hands-on and to contribute directly to the company’s mission. Leadership is given to those who show initiative and consistently deliver excellence. Work ethic and strong prioritization skills are important. All employees are expected to have strong communication skills. They should be able to concisely and accurately share knowledge with their teammates. ABOUT THE ROLE: The Sandbox service team at SpaceXAI builds and maintains a secure, scalable system that gives our models safe, controlled access to computational environments. This infrastructure powers critical workloads across training and product, enabling models to run code, build software, interact with tools, and even control applications with user interfaces. We provision containers and virtual machines on large-scale clusters, granting models interactive control over these remote environments. Our work spans the full stack: from orchestrating massive jobs and resource scheduling at the cluster level, to fine-tuning filesystem performance on nodes. The Sandbox service enables Grok to safely run and test code in real-time for user queries, and supports reinforcement learning in training, where models interactively explore tools ranging from compilers to productivity apps. BASIC QUALIFICATIONS: Expert knowledge of Rust, C++ or Go Familiarity with Python Deep experience with either Linux or Windows systems (familiarity with both is a strong plus) Experience with virtualisation and containerisation technologies (e.g., cgroups, KVM, gVisor, QEMU) Solid knowledge of the networking stack COMPENSATION AND BENEFITS: £107,000 -

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Ema (Enterprise Machine Assistant)
📍 San Francisco Bay Area• Full-time• $200K – $250K/yr
1mo 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. Role Overview As Chief of Staff to the CEO, you will be the strategic nerve center of the entire company — a true force-multiplier to Surojit Chatterjee (ex CPO Coinbase, VP Products at Google). Reporting directly to the CEO and based in Mountain View, CA (full co-location required), you will own the translation of the CEO's vision across Sales, Product, and the full organizational agenda — serving as connective tissue between the CEO and every critical function: EPD, GTM, Finance, HR, Legal, and the Board. This is a senior operating role for someone who has already done it — led strategy at scale, driven GTM at a high-growth technology company, and earned their stripes as an Engagement Manager or Associate Principal at a top-tier consulting firm (McKinsey, BCG, Bain) before stepping into industry. You are not here to learn the ropes; you are here to pull them. Ema is backed by top-tier investors (Accel, Section 32, and Prosus) and is building the Universal AI Employee for enterprises worldwide. This is a high-visibility, high-impact role at one of the most consequential AI companies in the world. Key Responsibilities CEO Leverage & Executive Operations Serve as Surojit's strat

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 160+ public exchanges globally and thousands of private exchanges 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 looking for a Staff Site Reliability Engineer (Production Engineer) to join our team. This is a hybrid role (onsite three days a week in San Jose, CA or another Zscaler office; remote can be considered for exceptional candidates) reporting to the Senior Manager, Site Reliability Engineering in the Zero Trust Exchange department. As a key member of the Zero Trust Exchange team, you will own the systems-level reliability and performance of Zscaler’s high-throughput bare-metal and cloud infrastructure processing tens of billions of daily transactions across a global, multi-region fleet. This is a software-first SRE role: you will write production-grade code and automation, drive the shift from reactive incident response, and bring engineering discipline to the systems-level work - OS, network and application debugging - that keeps the fleet operating safely at scale. What You’ll Do (Role Expectations) Maintain h

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21 days ago

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 160+ public exchanges globally and thousands of private exchanges 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 looking for a Staff Business System Analyst to join our team. This is a remote position within India reporting directly to the Director CRM & PRM Applications in the IT Business Apps department. In this pivotal role, you will act as a strategic link between business goals and technical execution, leading the design and delivery of scalable Sales Cloud / Experience Cloud solutions. You will partner deeply with cross-functional teams to translate complex GTM requirements into high-impact systems that drive efficiency and growth. What you’ll do (Role Expectations) Serve as a process and systems leader with deep ownership of how GTM strategy is operationalized across tools, workflows, and data models Propose and lead initiatives to implement new processes and optimize existing technologies and methodologies that enhance GTM experience and simplification Lead business and functional requiremen

REMOTEawsgitagile
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Zscaler
📍 California• Full-time• Remote• From $152K/yr
21 days ago

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 160+ public exchanges globally and thousands of private exchanges 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 looking for a Sr. Production Engineer to join our team. This role is available as a hybrid opportunity 3 days a week in San Jose, CA or Remote reporting to Production Engineering in the Cloud Infrastructure & Operations department. Join Zscaler to be a force multiplier for the reliability of a global platform processing 200+ billion transactions daily across tens of millions of enterprise users. In this role, you will provide the technical vision and hands-on execution to drive an "automation-first" culture across the company. By maturing our observability and architectural standards, you will directly reduce our Mean Time to Mitigate (MTTM) and shape the scalability of our globally distributed, multi-cloud infrastructure. What you’ll do (Role Expectations) Implement highly available, scalable infrastructure across AWS, GCP, and bare-metal environments Drive an "automation-first" culture by wr

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Zscaler
📍 Netherlands• Full-time• Remote
21 days ago

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 160+ public exchanges globally and thousands of private exchanges 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 looking for a Staff Site Reliability Engineer to join our Cloud Infrastructure & Operations team. This is a remote role based in the Netherlands, reporting to the Senior Director, Software Engineering. As a Staff SRE, you will leverage your expertise in Linux/UNIX System Administration to build scalable infrastructure and manage platforms like Kubernetes using automation and high security standards. You will troubleshoot complex Linux networking and security issues, manage firewall technologies, and ensure secure access across our global platforms and applications. What you’ll do (Role Expectations) Create and maintain highly scalable solutions based on KVM LINUX, Kubernetes, and Public Cloud Providers Analyze and troubleshoot systems performance and issues across the OS and Applications Maintain platform security and observability using nftables and robust monitoring tools Manage and deploy systems and s

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1mo ago

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 This is a zero-to-one Product Engineering role on Replit's Money team. You'll bring our financial partnerships alive from scoping to integrating and operating them so that the builders on Replit, and the Apps and Agents they ship can transact reliably anywhere in the world. Money at Replit isn’t traditional payments. Builders are publishing apps that earn revenue. Agents are spending and being paid for work. New protocols for agentic commerce now exist to power the future of commerce: Shared Payment Tokens, the Agentic Commerce Protocol (ACP), the Universal Commerce Protocol (UCP), the Machine Payments Protocol (MPP). Replit is one of the platforms that will define what they look like in practice and lower the barrier to entry. To make any of that real, we need someone who can sit between Replit engineering and our financial partners including billing platforms, payment processors, agentic-commerce protocol partners, tax and compliance vendors to turn signed contracts into live, reliable integrations. You'll be the engineer partners ask for, and the engineer the rest of Replit relies on when a new monetization surface needs to ship. This role is a fit if you like writing code and you also like being in the room when a partnership is being scoped, because you know that the design decisions made in that room are the ones that bind the integration for years. You will Take financial partnerships from zero-to-one: scope the integration with the partner, pressure-test data and protocol specs, design the system, build it, ship it, and operate it. Own the technical relationship with Replit's financial partners across the full lifecycle: billing platforms, payment processors, agentic-commerce protocol partners, t

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Who we are 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 Payment Intelligence is comprised of multiple product teams building AI-first solutions to some of our customers’ biggest challenges, including fraud/abuse ( Radar ), payment optimizations ( AuthBoost ), Disputes, Authentication, and merchant analytics. We’re a mix of machine engineering engineers and full-stack software engineers impacting ~every Stripe transaction, creating revenue opportunities for Stripe and our customers, and helping protect the broader ecosystem. We have the benefit and privilege of working on cutting edge technologies with incredible scale and reach while also working directly with our merchants every day to build the right products for their needs. What you'll do As a Staff Engineer on Payment Intelligence, you’ll work across our product portfolio to ensure we’re building in a consistent, efficient, and effective manner. Experience with large, distributed systems on the critical path will help candidates succeed, as will comfort working across the stack and interacting with ML teams and models. Responsibilities Define technical strategy for multiple experiences across the Payment Intelligence portfolio, with a focus on quality and performance Champion a quality-first engineering culture - establish standards, tooling, and processes that make it easy to ship high-quality code at scale Partner with some of Stripe’s largest merchants to co-build the future of payment-centric intelligence Partner cross-functionally

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Zscaler
📍 Bellevue• Full-time• From $180K/yr
21 days ago

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 160+ public exchanges globally and thousands of private exchanges 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 looking for a Senior Staff Rust Developer to join our Platform Convergence Team. This is a hybrid role based in San Jose, CA reporting to the Sr. Director, Software Engineering. Join us to build a new platform from the ground up that can scale hundreds of millions of users with high reliability and low latency. You will design and implement distributed system and core infrastructure components while collaborating closely with various stakeholders. What you’ll do (Role Expectations) Design and build a low-latency, high-throughput data forwarding plane using Rust, leveraging its async/await model for efficient I/O and service-oriented infrastructure Develop distributed, scalable systems with a focus on concurrency, fault tolerance, and messaging Implement and maintain gRPC-based APIs and services to integrate forwarding plane capabilities with control and orchestration layers Optimize system

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Modal
📍 San Francisco• Full-time
17 days ago

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We are looking for strong engineers with experience and interest in designing, building, and maintaining the novel, high-performance systems that make up our serverless platform. Specifically, you'll be working on Modal's machines layer: the fleet of bare metal and cloud hosts that every Function, Sandbox, and training job runs on, and the control plane that provisions, images, monitors, and repairs them. You'll automate the integration of new capacity from a growing set of hardware providers; from auditing and benchmarking hosts and clusters, to maintaining our machine images, configuring GPUs, RDMA, networking, and storage, and getting machines into production. You'll build the automation that keeps the fleet healthy without human intervention: detecting bad GPUs, thermals, and disks. You'll dig into whatever is between the hardware and the software that runs on

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17 days ago

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We are looking for a strong technical lead to guide the engineers designing, building, and maintaining the novel, high-performance systems that make up our serverless platform. You'll lead the team responsible for Modal's machines layer: the fleet of bare metal and cloud hosts that every Function, Sandbox, and training job runs on, and the control plane that provisions, images, monitors, and repairs them. You'll own the full lifecycle of a machine, from accepting and benchmarking new hardware from a growing set of providers, to network bring-up, kernel and image management, GPU and disk health tracking, and automated remediation of unhealthy hosts. You'll manage a team of 3–8 engineers while staying hands-on across the stack which involves BMCs, firmware, PXE, bootloaders, Linux networking, drivers, and distributed control-plane services, and you'll shape our long-

About the Role REMOTE IN INDIA We're looking for a software engineer to build the Kubernetes-native control plane that provisions and runs our GPU inference fleet. You'll design a manifest-driven API where the inference team declares what they need, whether that's a cluster, a model deployment, or a capacity change, and our controllers handle the reconciliation, provider/runtime selection, and lifecycle management underneath, so the inference team never has to know or care which specific serving stack, scheduler, or hardware pool is doing the work. You'll also build the systems that keep the fleet efficient, not just running, including defragmentation and rebalancing logic that consolidates scattered workloads back into contiguous capacity, and scheduling/bin-packing improvements that push GPU utilization up without hurting latency. The core value we're after is decoupling the people building on top of the platform from the operational and runtime complexity underneath, while squeezing more usable capacity out of the same hardware. You'll build the controllers, reconciliation loops, and self-service surface (API/CLI, not tickets) that make that decoupling real, plus the event-driven health, remediation, and utilization systems that keep it running and efficient without a human in the loop. Strong candidates have hands-on experience with Kubernetes controller/CRD patterns, have built or operated a platform API that abstracts multiple backends behind one interface, understand GPU scheduling and capacity efficiency (fragmentation, bin-packing, right-sizing), and think about GPU infrastructure as software to be engineered. A product mindset - you've built internal platforms or APIs consumed by other engineering teams and care about the developer experience of what you ship. You build it, you own it. You are not only responsible for delivering the software but also for operating and supporting it in production. Responsibilities Build the provisioning state machine

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