Staff AI Platform Engineer - Inference & Agentic Systems

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. About the role The App Runtime team is building a platform that lets every Snowflake user go from an idea to a live, deployed web application (Node.js first) in minutes. We own the end-to-end experience of building and running apps, from Cortex AI-assisted development to deployment in a secure, scalable infrastructure. Apps built on the platform inherit Snowflake's security, governance, lineage, and access controls by default. See Deploy Faster with Snowflake Apps . As a Staff/Principal Engineer, you will shape the product and its architecture. It’s a high leverage role - you will lead a team to scale and harden an early-stage, public-preview product. Your decisions will have a long-lasting impact on the future of Snowflake as an app platform. This role requires a unique combination of deep hands-on expertise in scalability, performance and security, great product instincts, customer obsession and the organizational influence to drive cross-team programs. Responsibilities Own the roadmap and technical decisions to evolve the public-preview platform into a production-grade one, adding features like horizontal scaling, cost efficiency via suspend/resume, support for stacks beyond Node.js, and stronger access and data-governance controls Stay deeply hands-on by authoring specs

About the Role: As a Staff Software Engineer on the ML Infrastructure team, you will collaborate closely with the Machine Learning and Product teams to build world-class machine learning inference platforms. These platforms power essential services like personalized recommendations, search, and content understanding across Tubi. A core responsibility of this team is developing and maintaining low-latency ML model serving systems that support Deep Learning, LLM, and Search models. This involves building self-service infrastructure and critical components such as the inference engine, feature store, vector store, and experimentation engine. You will improve the way we deploy and operate our services and even contribute to open-source projects. This role grants the architectural freedom to explore new frameworks, lead critical cross-functional projects, and transform the capabilities of our ML and Product teams. Responsibilities: Design and build scalable, high throughput, and low latency distributed systems using Scala Build reusable components and services that serve various ML applications like Personalization, Search, Ads and Exploration Partner closely with ML engineers to understand their challenges and limitations and develop scalable solutions to address them. Proactively recommend solutions to keep our ML Inference stack state of the art. Take a data driven approach to identifying & optimizing latency, cost, and efficiency of our infra. Lead large scale cross functional refactorings if necessary Mentor other engineers on the team on system design, effective incident management, interviewing, leveraging LLMs for work, etc. Collaborate with ML, Product, and cross functional engineering teams to define the long term vision and architecture for ML Infrastructure at Tubi. Your Background: Experience designing and building scalable, distributed systems in any modern backend language (e.g., Scala, Java, Python, Go, C++); experience with Scala or JVM b

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. Get to know the team The Developer Platform team at Auth0 (an Okta company) owns the surfaces developers use to build with Auth0 - APIs, SDKs, CLIs, and the tooling that shapes how developers experience identity. Software is increasingly built by developers working alongside AI agents, and that shift raises the bar on every interface we ship: APIs have to be consumable by agents, tools have to be discoverable, and our platform has to hold up when an agent - not just a person, is the one calling it. We're looking for an engineer who already builds with those skills. We move fast, we own problems end-to-end, and we care deeply about the developer experience we put in front of people. The opportunity We're hiring a Staff Software Engineer to build the platform surfaces that developers and AI agents use to configure, extend, and interact with Auth0. You'll work at the intersection of API platform design, developer tooling, and emerging standards like MCP (Model Context Protocol). You'll take on ambiguous, high-leverage problems alongside a group of strong senior and staff engineers, and you'll have real influence over how our platform is built for a world where agents are first-class consumers. What you'll be doing Design and build developer-facing platform surfaces - APIs, MCP tools, CLI integrations, that hold up whether the caller is a developer or an agent Own technical direction for key platform surfaces that make Auth0 consumable by agents Drive cross-cut

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 Streaming Foundations team builds services and operates data pipeline infrastructure to support event streaming, messaging, and analytics use cases. We are looking for a Software Engineer who is passionate about distributed systems, platform engineering, and solving data-intensive problems at scale. In this high-impact role, you will get to work with engineers throughout the organization to build foundational infrastructure that allows Auth0 to scale for years to come. What you’ll be doing Help set the technical direction for the team and influence the engineering roadmap for the Platform’s streaming capabilities Design and lead the implementation of our most complex and critical systems for data-intensive use cases. Research and champion new technologies and architectural patterns to solve strategic challenges and scale the platform. Lead and influence cross-functional initiatives, ensuring technical alignment and successful execution across multiple teams. Improve the operational posture of our systems by designing for observability, reliability, and scalability, and by mentoring others in operational best practices. Coach and mentor senior engineers and act as a technical leader across the engineering organization. Collaborate with different stakeholders like product teams whenever needed. What you’ll bring to our teams 7+ years of software development experience in a fast-paced, agile environment Experience working with Golang or Java is preferred H

About the Role: The Growth team is responsible for building and optimizing the UI/UX across all Web and OTT applications at Tubi. The team primarily focuses on implementing features related to full funnel user acquisition and growth, including SEO user registration, onboarding, and account management. As a Staff Engineer (L5) on this team, you act as the technical leader for one or more Growth areas. You own the technical architecture and direction, solve ambiguous problems that few others can, and influence cross-functional teams across multiple pods. You will work closely with Product and Design to develop cutting-edge, experiment-driven features, while driving the front-end architecture that ensures performance and scalability for millions of users. You will be working with React, Node.js, GitHub Actions, Terraform, and CDN infrastructure to build and deploy high-performance applications that reach millions of users. This is a hybrid role based out of our Toronto office. You must be willing to travel to our Toronto office two days/week. What You'll Do: Own the technical roadmap and architecture for a Growth area with large amounts of ambiguity: driving direction across web, mobile web, and smart TV platforms, and influencing the team to invest in new projects. Solve challenging, ambiguous problems with a focus on scalability and performance; proactively identify systemic issues and propose innovative solutions. Lead and drive innovation in building experiment-driven features; independently design, implement, and interpret a series of A/B experiments that move growth metrics. Lead and coordinate major rollouts and releases: including cross-team coordination, migrations, and phased releases of major initiatives across Web and OTT apps. Establish team-wide quality and engineering standards; set the bar for code quality and front-end best practices. Identify and implement improvements in shared UI components, platform-specific optimizations, and overall fr

About the Role: We're hiring Senior and Staff Data Platform Engineers to join the Data Infrastructure teams in Toronto. Together these teams own the infrastructure that processes billions of events per day: Spark-on-Kubernetes, Flink and Kinesis pipelines, a multi-petabyte Delta Lake, a large-scale MemoryDB feature store, Databricks multi-environment operations, and the catalog and lifecycle systems that govern it. The team is small and senior. Each engineer owns major platform components: you design it, build it, and support it in production. This is a hybrid-role based out of our Toronto office. You must be willing to travel to our Toronto office two days/week. What You'll Do: Spark-on-Kubernetes — EKS-based compute platform for Spark workloads: cluster configuration, Pod Identity IAM, job environment setup, Kustomize overlays, and shadow canary validation Event ingestion — Rust services and Flink jobs processing billions of events per day over Kinesis; throughput, reliability, on-call response, and AI-assisted operational tooling to reduce toil Platform infrastructure — Terraform modules for environment provisioning, cross-account AWS IAM, ARC runner infrastructure, and CI/CD for data platform changes Feature store and ML compute — Flink-based real-time feature pipelines feeding a large-scale MemoryDB cluster; GPU capacity governance and Databricks multi-environment operations for ML training workloads Workflow orchestration and CDC — Airflow-based DAG deployment, change data capture pipeline operations, and data quality monitoring Your Background: 3+ years building and operating production data platform infrastructure at the cluster or platform level, across Spark, Flink, Kinesis, Kubernetes, or equivalent Deep experience in at least one of: Spark-on-K8s cluster operations, Rust-based data or systems engineering, Kubernetes platform engineering and IaC, or data catalog and governance tooling Production AWS experience or equivalent: EKS, S3, Kinesis, and mu