At ClickUp, we're building the future of work: the first truly converged AI workspace unifying tasks, docs, chat, calendar, and enterprise search, all supercharged by context-driven AI. We are an AI-native company. Every team member is expected to leverage AI daily, and we evaluate AI fluency as part of our hiring process. Join us and help redefine what's possible. 🚀 Role Overview: We are seeking a skilled and experienced Senior AI Engineer – AI Platform to join our ClickUp Engineering team. In this role, you will play a critical part in both building the core AI platform and directly applying large language models (LLMs) to deliver intelligent features across ClickUp. You will focus on backend systems that enable scalable, reliable, and secure AI-powered capabilities, while also working hands-on with LLMs to solve real user problems and drive product innovation. Key Responsibilities: Architect, design, and implement scalable AI platform services that support the deployment, orchestration, and lifecycle management of LLMs and other AI models. Apply LLMs and other AI technologies directly to build and enhance ClickUp’s intelligent features, working closely with product and engineering teams to deliver impactful solutions. Build and maintain robust APIs and backend systems that enable seamless integration of AI-powered features into ClickUp’s core platform. Develop infrastructure for model serving, monitoring, logging, and automated evaluation to ensure high reliability and performance of AI services in production. Integrate with multiple LLM providers (e.g., OpenAI, Anthropic, Google) and manage model selection, routing, and fallback strategies for optimal performance and cost. Drive the adoption of best practices in AI privacy, security, and compliance, including data anonymization, secure data handling, and regulatory adherence. Optimize platform performance, scalability, and cost-efficiency, leveraging cloud-native technologies and distributed systems. Stay curre
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At ClickUp, we're building the future of work: the first truly converged AI workspace unifying tasks, docs, chat, calendar, and enterprise search, all supercharged by context-driven AI. We are an AI-native company. Every team member is expected to leverage AI daily, and we evaluate AI fluency as part of our hiring process. Join us and help redefine what's possible. 🚀 Role Overview: We are seeking a highly skilled Staff AI Engineer – AI Platform to join our ClickUp Engineering team. In this role, you will play a critical part in both building the core AI platform and directly applying large language models (LLMs) to deliver intelligent features across ClickUp. You will focus on backend systems that enable scalable, reliable, and secure AI-powered capabilities, while also working hands-on with LLMs to solve real user problems and drive product innovation. Key Responsibilities: Architect, design, and implement scalable AI platform services that support the deployment, orchestration, and lifecycle management of LLMs and other AI models. Apply LLMs and other AI technologies directly to build and enhance ClickUp’s intelligent features, working closely with product and engineering teams to deliver impactful solutions. Build and maintain robust APIs and backend systems that enable seamless integration of AI-powered features into ClickUp’s core platform. Develop infrastructure for model serving, monitoring, logging, and automated evaluation to ensure high reliability and performance of AI services in production. Integrate with multiple LLM providers (e.g., OpenAI, Anthropic, Google) and manage model selection, routing, and fallback strategies for optimal performance and cost. Drive the adoption of best practices in AI privacy, security, and compliance, including data anonymization, secure data handling, and regulatory adherence. Optimize platform performance, scalability, and cost-efficiency, leveraging cloud-native technologies and distributed systems. Stay current with ad
Who We Are Addepar is a global data and AI platform empowering investment professionals to turn complex financial information into actionable intelligence. Addepar unifies portfolio, market and client data in a total portfolio view and delivers AI-powered insights within investment and client workflows. More than 1,400 firms in nearly 60 countries use Addepar to manage and advise on nearly $9 trillion in assets. Its open platform integrates with nearly 650 software, data and consulting partners to power end-to-end investment operations across firms of all sizes and complexity. Addepar supports clients worldwide with offices in New York City, Salt Lake City, London, Edinburgh, Pune, Dubai, Geneva, Singapore and São Paulo. The Role We are currently seeking a Staff Software Engineer, Infrastructure to join the AI Platform team that powers seamless insights and interaction through natural language and data intelligence across our AI products. As a Staff Software Engineer, you’ll architect, build, and operate the backend and platform systems that power AI Platform. You’ll work across service design, distributed systems, cloud infrastructure, event-driven processing, observability, CI/CD, and production reliability, helping shape the technical direction of a platform that supports scalable, client-facing AI experiences. This role requires a strong software engineering foundation combined with deep infrastructure and systems thinking. We are looking for an engineer who can write high-quality production code, make sound architectural tradeoffs, and own platform capabilities end-to-end — not someone focused only on scripting, cloud configuration, or infrastructure tooling in isolation. You will collaborate closely with frontend, product, and AI/ML engineers to deliver reliable, secure, and scalable systems that align with Addepar’s standards of performance, resilience, and trust. Applicants must have legal authorization to work in the country where this role is based o
Ready to do the most impactful work of your career? At Coinbase , we are uncompromising on our mission to increase economic freedom. The bar is high, the environment is intense, and we like it that way. This isn't a place for complacency, it’s a place to be pushed past your perceived limits. If you're ready to build the future of finance alongside people who refuse to settle for "good enough," you belong here. Coinbase is a remote-first, but not remote-only company. Expect to get together quarterly for intense in-person working sessions called “surges.” learn more about working at Coinbase . As a Senior Software Engineer on the AI Platform team within the Platform group, you'll build and operate the LLM and agent infrastructure that every team at Coinbase depends on. This team owns the company's single path to large language models and the full agent lifecycle: build, deploy, run, observe, and improve. You'll lead multi-quarter technical initiatives across the platform, from gateway and runtime systems to knowledge bases and applied AI agents, directly shaping how Coinbase scales AI across the organization. What you'll do: Own the architecture and delivery of core platform systems including the LLM Gateway (60+ models, auth, PII redaction, fallbacks, cost optimization), AI Hub, and agent runtime with microVM sandboxes and governed MCP gateway Drive the design and implementation of Knowledge Base infrastructure, connecting data sources to auto-provisioned vector and markdown stores queryable by any agent Lead AI FinOps capabilities including spend attribution, governance, and cost optimization across all AI workloads company-wide Partner across engineering, security, legal, finance, product, and external partners at frontier labs and major cloud providers to ship high-impact platform capabilities Build evaluation and observability tooling including LLM-as-judge harnesses, full tracing, and feedback loops that let subject matter experts refine production a
The AI platform is responsible for all AI infrastructure across Datadog. Our mission is to provide tools and platforms that enable data scientists and engineers to conduct large-scale training and inference with ease. We support products such as Bits AI , LLMObs and all our AI research . As an engineering manager for the Evaluation & Annotation team, you’ll join a new and fast growing team and organization. You will support building and scaling the team, define our technical vision and help shape the roadmap. Your team will lead the charge on multiple critical technical challenges: AI model evaluation both offline and online, designing tooling and processes around human annotation, and establishing the standard around synthetics and AI generated datasets. You’ll work closely with sister teams in the AI platform organization ensuring a seamless AI development cycle. You’ll also partner with the Applied AI org and with Datadog infrastructure & tooling teams to build out systems from the ground up. At Datadog, we place value in our office culture - the relationships that it builds, the creativity it brings to the table, and the collaboration of being together. We operate as a hybrid workplace to ensure our employees can create a work-life harmony that best fits them. What You’ll Do: Manage and grow the Evaluation & Annotation team, directly managing 4-6 engineers Define our technical roadmap in alignment with AI platform goals and the Applied AI team roadmap. Work with our core platform teams to tailor Datadog's storage and data pipelines to our needs Create a strong team culture aligned with our engineering standards and our customer focus Participate in hands-on work: Code reviews, design reviews and some coding Who You Are: A Software Engineer at heart with a previous experience leading software engineering teams, as a tech lead or people manager Excellent leader with strong interpersonal skills, and the
The AI platform is responsible for all AI infrastructure across Datadog. Our mission is to provide tools and platforms that enable data scientists and engineers to conduct large-scale training and inference with ease. We support products such as Bits AI , LLMObs and all our AI research . As an engineering manager for the Training & Serving team, you’ll join a new and fast growing team and organization. You will support building and scaling the team, define our technical vision and help shape the roadmap. Your team will lead the charge on multiple critical technical challenges: distributed training of foundation models, serving at scale, designing the user experience. You’ll work closely with sister teams in the AI platform organization ensuring a seamless AI development cycle. You’ll also partner with the Applied AI org and with Datadog infrastructure & tooling teams to build out systems from the ground up. At Datadog, we place value in our office culture - the relationships that it builds, the creativity it brings to the table, and the collaboration of being together. We operate as a hybrid workplace to ensure our employees can create a work-life harmony that best fits them. What You’ll Do: Manage and grow the Training & Serving team, directly managing 10+ engineers Define our technical roadmap in alignment with AI platform goals and the Applied AI team roadmap. Work with our core platform teams to tailor Datadog's storage, infrastructure and data pipelines to our needs Create a strong team culture aligned with our engineering standards and our customer focus Participate in hands-on work: Code reviews, design reviews and some coding Who You Are: Previous experience (1+ years) leading software engineering teams, as a tech lead or people manager Strong technician with a mix of backend, data engineer and infrastructure experience who is interested in remaining a hands-on leader Excellent leader with strong
This position is based in Vancouver, BC , within Diligent’s Technical Center of Excellence. We are currently hiring candidates who are based in or able to work from Vancouver . Software Engineer — Platform AI Service Levels: Software Engineer II Senior Software Engineer Staff Software Engineer Location: Vancouver Position Overview As a Software Engineer on Diligent's Platform AI team, you'll help design, build, and operate the core services that power AI-driven capabilities across Diligent's global product suite. You'll build secure, scalable, serverless services on AWS that translate AI research and models into commercial-quality, production-ready solutions — enabling customers to derive insights from their governance data. You'll work closely with AI researchers, product managers, and other engineering teams, owning your services end-to-end: architecture, implementation, deployment, and monitoring. The team operates with a strong AI-augmented engineering culture — using AI tools to accelerate coding, testing, debugging, and delivery — while applying sound judgment about when and how to apply them. Key Responsibilities Design and implement secure, scalable, fault-tolerant, high-performing solutions using AWS serverless technology — event-driven, highly observable, and built with infrastructure as code. Collaborate with AI researchers/engineers to translate AI and LLM capabilities into robust, production-grade services, and help other teams integrate them. Build and maintain the pipelines needed to deploy, monitor, and manage AI services at scale — observable, resilient, and cost-effective. Use AI-powered development tools (code assistants, test generation, architecture exploration) responsibly to accelerate delivery and improve quality, always validating outputs. Participate in architecture discussions and design reviews, and contribute to product design by understanding customer problems — especially where AI can offer a breakthrough solution. Work in
Role Description We are seeking a Senior Manager, Data Engineering to lead the team responsible for Dropbox’s underlying data foundations that power our business as a whole. This is a hands-on engineering leader who owns the pipelines and data products that Product, GTM, Finance, and the CTO organization depend on to make decisions. In this role, you will lead and grow a team of data engineers building and operating our ingestion, transformation, orchestration, and serving layers, as well as the self-serve analytics substrate that lets partner teams answer their own questions without bespoke engineering work. The ideal candidate is a deeply technical, product-minded engineering leader who can hold a high bar on system reliability and data quality while partnering closely with Data Science, Business Intelligence Engineering, Analytics, and Product to turn fragmented, ticket-driven data work into durable, reusable data products. Our Engineering Career Framework is viewable by anyone outside the company and describes what’s expected for our engineers at each of our career levels. Check out our blog post on this topic and more here . Responsibilities Data Quality & Observability: Establish and enforce a rigorous data quality culture: lineage, freshness monitoring, anomaly detection, and outcome-oriented, gaming-resistant quality metrics. Self-Serve Platform: Lead the engineering of the self-serve analytics substrate, reducing bespoke request volume and increasing partner-team autonomy. Cost & Efficiency: Own the unit economics of the data platform — compute and storage efficiency — and drive measurable improvements without sacrificing reliability. Cross-Functional Partnership: Partner deeply with Data Science, BIE, Analytics, Product, Data Platform, and the CTO org to define the semantic layer, modeling standards, and data contracts that make downstream work trustworthy and fast. Engineering Culture: Establish rigorous engineering practices
Role Description We are seeking a Senior Manager, Data Engineering to lead the team responsible for Dropbox’s underlying data foundations that power our business as a whole. This is a hands-on engineering leader who owns the pipelines and data products that Product, GTM, Finance, and the CTO organization depend on to make decisions. In this role, you will lead and grow a team of data engineers building and operating our ingestion, transformation, orchestration, and serving layers, as well as the self-serve analytics substrate that lets partner teams answer their own questions without bespoke engineering work. The ideal candidate is a deeply technical, product-minded engineering leader who can hold a high bar on system reliability and data quality while partnering closely with Data Science, Business Intelligence Engineering, Analytics, and Product to turn fragmented, ticket-driven data work into durable, reusable data products. Responsibilities Data Quality & Observability: Establish and enforce a rigorous data quality culture: lineage, freshness monitoring, anomaly detection, and outcome-oriented, gaming-resistant quality metrics. Self-Serve Platform: Lead the engineering of the self-serve analytics substrate, reducing bespoke request volume and increasing partner-team autonomy. Cost & Efficiency: Own the unit economics of the data platform — compute and storage efficiency — and drive measurable improvements without sacrificing reliability. Cross-Functional Partnership: Partner deeply with Data Science, BIE, Analytics, Product, Data Platform, and the CTO org to define the semantic layer, modeling standards, and data contracts that make downstream work trustworthy and fast. Engineering Culture: Establish rigorous engineering practices — code review, testing, CI/CD for data, incident response, and postmortems — and champion the effective, measured use of AI coding tools to improve engineering productivity. Team Leadership: Lead, mentor, and grow
Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title and Summary Vice President, Software Engineering Overview Decision Stream is Mastercard's next-generation AI-native decisioning platform, designed to power intelligent, real-time decisions across fraud, authentication, payments, and risk. Built with a startup mindset and enterprise-scale ambition, the platform combines innovation, speed, and engineering excellence to redefine decisioning across Mastercard's global ecosystem. We are seeking a visionary and hands-on VP of Software Engineering to help build and scale the platform. This leader will partner closely with Product, Architecture, AI, and Platform Engineering teams to drive technology strategy, architecture, engineering execution, and organizational growth. What You'll Do Lead Through Technical Excellence • Serve as a senior technology leader and role model for engineering teams. • Drive architecture, design, and technology decisions across distributed systems, streaming, AI, and cloud-native platforms. • Engage deeply with engineers, architects, and product leaders to solve complex technical challenges. • Influence engineering standards, software quality, and operational excellence. Build and Scale the Platform • Help shape and deliver a highly scalable, resilient, and secure decisioning platform operating at Mastercard scale. • Balan
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 As a software engineering intern, you will work closely with leading experts in the field of machine learning, robotics, and software. Depending on your skill sets and areas of interest, you will work on some or all of the following: Data Platform, Onboard Systems, ML Infrastructure, Simulation, or Technical Infrastructure teams. About the Work Depending on your skill set and areas of interest you will work on some or all of the following: Data Platform: The Data Platform serves as a comprehensive management system for Nuro AI Driver's data, labels, and metrics, facilitating seamless access functionality. The team focuses on data annotation across various domains, including 2D/3D perception, mapping, behavior trajectory, and language/text. It also handles data ingestion and mining, employing methods such as heuristics and embedding search. Additionally, the platform supports the autonomy evaluation infrastructure by provid
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 Our software team is growing, and we are looking for talented engineers who are graduating by December 2026 to join us and be instrumental to one of the following areas: Data Platform, Onboard Systems, ML Infrastructure, Simulation, or Technical Infrastructure teams. About the Work Depending on your skill set and areas of interest you will work on some or all of the following: Data Platform: The Data Platform serves as a comprehensive management system for Nuro AI Driver's data, labels, and metrics, facilitating seamless access functionality. The team focuses on data annotation across various domains, including 2D/3D perception, mapping, behavior trajectory, and language/text. It also handles data ingestion and mining, employing methods such as heuristics and embedding search. Additionally, the platform supports the autonomy evaluation infrastructure by providing detailed introspection. Onboard Systems: Our onboard s
Staff Software Engineer, AI Platform — Chicago, Israel. Apply via Workday.
Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. Platform Engineer An individual contributor who will serve as a hands-on technical member of the SMAI Platform Engineering team. In this role, you will help build, operate, and maintain the platforms that power Micron's analytics and AI workloads. You will contribute to platform reliability and scalability through day-to-day engineering, collaborative problem solving, and close partnership with solution architects, project teams, and multi-functional partners. Responsibilities: Collaborate with global platform teams, customers, partners, and vendors to deliver effective technical solutions. Know the latest platform roadmaps, emerging technologies, and new service offerings; evaluate and recommend adoption opportunities. Partner with solution architects to design, implement, and optimize solutions across IaaS, PaaS, SaaS, and Infrastructure as Code (Terraform). Document findings, operational procedures, guidelines, and reusable patterns while providing feedback to vendors and internal teams. Deliver high-quality platform support by managing customer requests, maintaining service standards, and implementing controlled platform adjustments. Monitor platform performance, observability, costs, and resource utilization to identify optimization opportunities and improve reliability. Collaborate with multi-functional teams to ensure seamless operations, scalable architectures, and automation, including AI-driven business solutions. Implement and m
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