Ai Platform Engineer Jobs

About the Team The Applied AI Engineering team is responsible for helping customers turn frontier AI capabilities into real products, workflows, and business impact. We act as trusted technical partners across solution design, architecture, implementation, evaluation, and adoption, working alongside customers to build and scale effective AI applications with OpenAI’s technologies. The Codex Applied AI Engineering team focuses on helping organizations transform how software is built with AI. We partner directly with engineering teams and technical leaders to integrate Codex into their software development lifecycle — from identifying high-impact use cases and designing AI-enabled workflows to implementation, evaluation, and scaled adoption. Our work helps ensure AI-powered software development is effective, reliable, secure, and deeply integrated into how engineering organizations operate. About the Role We are seeking an experienced technical leader to join as Manager, Applied AI Engineering (Codex) , leading a team of Applied AI Engineers responsible for driving successful Codex adoption across strategic customers. Your team will work hands-on with customer engineering organizations to design and build AI-enabled development workflows, solve complex implementation challenges, and establish scalable patterns for AI-powered software development. As a manager, you will shape how these technical engagements operate at scale — setting strategy, coaching engineers, determining where the team can have the greatest impact, and ensuring consistently strong execution across customers. You will serve as both a people leader and senior technical advisor, partnering closely with Sales, Product, Research, and Engineering to translate customer needs and real-world usage into better technical approaches, reusable patterns, and product insights. Success in this role will be measured by meaningful and sustained Codex adoption, successful customer outcomes, and the creation of repeat

The pay range is $132,000.00 - $238,000.00 Pay is based on several factors which vary based on position. These include labor markets and in some instances may include education, work experience and certifications. In addition to your pay, Target cares about and invests in you as a team member, so that you can take care of yourself and your family. Target offers eligible team members and their dependents comprehensive health benefits and programs, which may include medical, vision, dental, life insurance and more, to help you and your family take care of your whole selves. Other benefits for eligible team members include 401(k), employee discount, short term disability, long term disability, paid sick leave, paid national holidays, and paid vacation. Find competitive benefits from financial and education to well-being and beyond at https://corporate.target.com/careers/benefits . JOIN TARGET AS A LEAD FULL STACK ENGINEER - ADVANCED AI About us: Working at Target means helping all families discover the joy of everyday life. We bring that vision to life through our values and culture. Learn more about Target here . About the role Target’s Advanced AI team

NVIDIA has continuously reinvented itself over two decades. Our invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing. NVIDIA is a “learning machine” that constantly evolves by adapting to new opportunities that are hard to solve, that only we can address, and that matter to the world. This is our life’s work, to amplify human creativity and intelligence. Make the choice to join us today. Design-for-Test Engineering at NVIDIA works on groundbreaking innovations involving crafting creative solutions for DFT architecture, verification and post-silicon validation on some of the industry's most complex semiconductor chips. What you'll be doing: As a senior member in our team, you will work with pre-silicon and post-silicon data analytics - visualization, insights and modeling. Design and uphold sturdy data pipelines and ETL processes for the ingestion and processing of DFX Engineering data from various origins Lead engineering efforts by collaborating with cross-functional teams (execution, analytics, data science, product) to define data requirements and ensure data quality and consistency You will work on hard-to-solve problems in the Design For Test space which will involve application of algorithm design, using statistical tools to analyze and interpret complex datasets and explorations using Applied AI methods. In addition, you will help develop and deploy DFT methodologies for our next generation products using Gen AI solutions. You will also help mentor junior engineers on test designs and trade-offs including cost and quality. What we need to see: BSEE (or equivalent experience) with 5+, MSEE with 3+, or PhD wi

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why this role? Design and implement novel research ideas, ship state of the art models to production, and maintain deep connections to academia and the government. We have one of the highest ratio of compute to engineers in the world. We do not delineate strongly between engineering and research. Everyone will contribute to writing production code and conducting research depending on individual interest and organizational needs. We have all the compute, data, and talent available for you to do your best work. As a Member of Technical Staff - Sovereign AI, you will: Design, build and scale agentic AI systems for serving mission critical use cases. Research, implement, and experiment with ideas on our supercompute and data infrastructure. Learn from and work with the best researchers in the field. Execute across the full AI stack and ship products to serve public interest. You may be a good fit if you have: Canadian citizenship and eligibility for security clearance ( required for this role ). Extremely strong software engineering skills. Proficiency in Python and related ML frameworks. Experience training, evaluating, and using (

Our mission and customers: We are creating the freedom for SMEs to succeed by delivering Europe's leading finance workspace with banking at its core, augmented by financial tools. We are proud to be rated 4.8 on Trustpilot, based on 55,000+ reviews. Our culture puts customer satisfaction at the core of what we do, as proven by our Net Promoter Score of 75 (more about our culture here). Our journey: Founded in 2017 by Alexandre and Steve, Qonto has grown to 1,600+ Qontoers serving over 600,000+ customers across 8 European countries. We have been profitable since 2023, and we are just getting started. Our beliefs: We hire for skills and potential. With 80+ nationalities, 45% women, of which 56% of women in our leadership team, diversity isn't a program; It's who we are. We've built a discrimination-free hiring process because the best teams are built on merit. AI at Qonto: AI is deeply embedded in how we work (here) - Every Qontoer gets unlimited access to the best AI tools. We want people who experiment without waiting for permission, push AI beyond the obvious, know when to trust it, and when to question it. ------------------------------------------------------------------------------------------------------ Join us as a Staff Machine Learning Engineer on our AI Product team to build and ship customer-facing AI for 600,000+ business customers. You'll combine Generative AI with proven machine-learning techniques to create products with measurable impact — adoption, faster task completion, user satisfaction — while ensuring reliability, privacy, and continuous monitoring in production. ➡️ What you'll do Develop ML models end-to-end: From understanding product requirements to training, evaluating, and deploying models in production. You design, iterate, and ship — not just prototype. Integrate ML into the product ecosystem: Align with Product Managers, Data Engineers, and Backend Engineers to ensure your models are seamlessly embedded in Qonto's financial services.

For over 20 years, Smartsheet has empowered teams to manage work seamlessly and scale solutions smarter. Now, in our most ambitious chapter yet, we are uniting human teams with AI agents. By orchestrating the work agents do best, automating manual tasks and uncovering insights at scale, we create the space for people to focus on what truly matters: judgment, creativity, and big thinking. That is magic at work, and it’s what we show up for every day. You independently lead the most complex AI deployments Smartsheet undertakes. You own the full engagement lifecycle from technical discovery through production deployment through solutions org handoff. You architect multi-agent solutions, design client-personalized MCP resource packs, and build the Deployment Kits that transform how 200+ solutions consultants and partners operate. You mentor junior FDEs, drive the intelligence loop, and present field findings at weekly Applied AI strategy sessions. You are building a function, not filling a role. What You Will Do Lead complex, multi-system AI deployments end-to-end scope, architect, build, validate, and manage the customer relationship throughout. Own the AI workshop program for your pod, customize modules per customer, lead technical sessions, translate outputs into production requirements, evolve content from field learning. Architect multi-agent solutions selecting the right coordination pattern for each customer’s workflow characteristics and compliance requirements. Design client-specific and industry-specific MCP resource packs that serve personalized intelligence from the server so every connected AI surface gets smarter for that customer automatically. Own Deployment Kit quality for your pod. If a kit is not documented well enough for a solutions consultant with no engineering background to follow, it isn’t done. Lead Solutions Enablement Sprints: transfer AI deployment patterns to solutions consultants and partners with training materials and certification crite

For over 20 years, Smartsheet has empowered teams to manage work seamlessly and scale solutions smarter. Now, in our most ambitious chapter yet, we are uniting human teams with AI agents. By orchestrating the work agents do best, automating manual tasks and uncovering insights at scale, we create the space for people to focus on what truly matters: judgment, creativity, and big thinking. That is magic at work, and it’s what we show up for every day. You independently lead the most complex AI deployments Smartsheet undertakes. You own the full engagement lifecycle from technical discovery through production deployment through solutions org handoff. You architect multi-agent solutions, design client-personalized MCP resource packs, and build the Deployment Kits that transform how 200+ solutions consultants and partners operate. You mentor junior FDEs, drive the intelligence loop, and present field findings at weekly Applied AI strategy sessions. You are building a function, not filling a role. What You Will Do Lead complex, multi-system AI deployments end-to-end scope, architect, build, validate, and manage the customer relationship throughout. Own the AI workshop program for your pod, customize modules per customer, lead technical sessions, translate outputs into production requirements, evolve content from field learning. Architect multi-agent solutions selecting the right coordination pattern for each customer’s workflow characteristics and compliance requirements. Design client-specific and industry-specific MCP resource packs that serve personalized intelligence from the server so every connected AI surface gets smarter for that customer automatically. Own Deployment Kit quality for your pod. If a kit is not documented well enough for a solutions consultant with no engineering background to follow, it isn’t done. Lead Solutions Enablement Sprints: transfer AI deployment patterns to solutions consultants and partners with training materials and certification crite

For over 20 years, Smartsheet has empowered teams to manage work seamlessly and scale solutions smarter. Now, in our most ambitious chapter yet, we are uniting human teams with AI agents. By orchestrating the work agents do best, automating manual tasks and uncovering insights at scale, we create the space for people to focus on what truly matters: judgment, creativity, and big thinking. That is magic at work, and it’s what we show up for every day. The Opportunity Asia-Pacific is one of the fastest-moving enterprise AI markets in the world — and the buyers, competitive dynamics, and adoption patterns in the region are distinct from any other geography Smartsheet serves. Enterprises in APJ are evaluating AI capabilities with urgency, but their buying criteria, integration ecosystems, and trust frameworks differ meaningfully from those in North America or Europe. Smartsheet needs an AI product marketing leader embedded in the region who can translate our global AI narrative into locally resonant positioning that wins. As a Sr Product Marketing Manager on the AI GTM Strategy team, you will be the in-region AI product marketing partner for Smartsheet's APJ sales organization. You will own the regional activation of Smartsheet's AI narrative — including organizational intelligence, agentic workflows, and Model Context Protocol (MCP) positioning — ensuring APJ field teams can lead differentiated AI conversations with enterprise buyers across the region. This is not a generalist PMM role. You will own the intersection of AI product marketing and regional field activation across APJ, working at the pace of a rapidly evolving product surface and a field organization operating in one of the most competitive enterprise software markets globally. This remote eligible role is based in APJ and will report to the VP, AI GTM Strategy. What You Will Own AI Narrative Activation — APJ Execute the regional activation of Smartsheet's global AI narrative across APJ field teams, a

For over 20 years, Smartsheet has empowered teams to manage work seamlessly and scale solutions smarter. Now, in our most ambitious chapter yet, we are uniting human teams with AI agents. By orchestrating the work agents do best, automating manual tasks and uncovering insights at scale, we create the space for people to focus on what truly matters: judgment, creativity, and big thinking. That is magic at work, and it’s what we show up for every day. You independently lead the most complex AI deployments Smartsheet undertakes. You own the full engagement lifecycle from technical discovery through production deployment through solutions org handoff. You architect multi-agent solutions, design client-personalized MCP resource packs, and build the Deployment Kits that transform how 200+ solutions consultants and partners operate. You mentor junior FDEs, drive the intelligence loop, and present field findings at weekly Applied AI strategy sessions. You are building a function, not filling a role. You will work remotely from Germany and will be reporting to Sr. Director, Engineering You Will: Lead complex, multi-system AI deployments end-to-end scope, architect, build, validate, and manage the customer relationship throughout. Own the AI workshop program for your pod, customize modules per customer, lead technical sessions, translate outputs into production requirements, evolve content from field learning. Architect multi-agent solutions selecting the right coordination pattern for each customer's workflow characteristics and compliance requirements. Design client-specific and industry-specific MCP resource packs that serve personalized intelligence from the server so every connected AI surface gets smarter for that customer automatically. Own Deployment Kit quality for your pod. If a kit is not documented well enough for a solutions consultant with no engineering background to follow, it isn't done. Lead Solutions Enablement Sprints: transfer AI deployment patterns to so

About the Team The Applied AI Engineering team partners closely with customers to help them turn frontier AI capabilities into real products, workflows, and business impact. We act as trusted technical partners across strategy, solution design, architecture, implementation, evaluation, and adoption, working alongside customers to build and scale effective AI applications with OpenAI’s technologies. The Digital Natives segment serves technology and software companies that are building AI into the core of their products and businesses. These customers are often highly technical, move quickly, and are among the earliest adopters of OpenAI’s newest capabilities. Our Applied AI Engineers work directly with their engineering, product, and technical leadership teams to identify high-impact opportunities, solve complex technical challenges, and bring ambitious AI applications into production. About the Role We are seeking a Manager, Applied AI Engineering (Digital Natives) to lead the team responsible for the technical success of our most strategic technology and software customers in the Americas. In this role, you will lead a team of Applied AI Engineers who work hands-on with customers to design, build, evaluate, and scale AI applications. You will help determine where deep technical partnership can unlock the greatest customer and business impact, while developing repeatable approaches that allow the team to support a broad and fast-moving customer segment. As a manager, you will set the strategy and operating model for the team, coach and develop engineers, and serve as a senior technical partner to customers and internal stakeholders. You will work closely with Sales, Product, Engineering, and Research to connect what we learn from customers with OpenAI’s product direction and help customers take advantage of our newest capabilities. Success in this role will be measured by meaningful production applications, sustained adoption and usage, strong customer outcomes, and

About the Team The Applied AI Engineering team partners closely with customers to help them turn frontier AI capabilities into real products, workflows, and business impact. We act as trusted technical partners across strategy, solution design, architecture, implementation, evaluation, and adoption, working alongside customers to build and scale effective AI applications with OpenAI’s technologies. The Digital Natives segment serves technology and software companies that are building AI into the core of their products and businesses. These customers are often highly technical, move quickly, and are among the earliest adopters of OpenAI’s newest capabilities. Our Applied AI Engineers work directly with their engineering, product, and technical leadership teams to identify high-impact opportunities, solve complex technical challenges, and bring ambitious AI applications into production. About the Role We are seeking a Manager, Applied AI Engineering (Digital Natives) to lead the team responsible for the technical success of our most strategic technology and software customers in the Americas. In this role, you will lead a team of Applied AI Engineers who work hands-on with customers to design, build, evaluate, and scale AI applications. You will help determine where deep technical partnership can unlock the greatest customer and business impact, while developing repeatable approaches that allow the team to support a broad and fast-moving customer segment. As a manager, you will set the strategy and operating model for the team, coach and develop engineers, and serve as a senior technical partner to customers and internal stakeholders. You will work closely with Sales, Product, Engineering, and Research to connect what we learn from customers with OpenAI’s product direction and help customers take advantage of our newest capabilities. Success in this role will be measured by meaningful production applications, sustained adoption and usage, strong customer outcomes, and

Who We Are Notion is the collaborative AI workspace where teams and agents think together . We're building one place where your knowledge, projects, meetings, and AI tools live side by side, so work is faster, clearer, and less fragmented. Millions of individuals, small teams, and large companies run their work on Notion. Notinos (our employees) are customer zero in bringing this future of work to life. We care about craft, building things that last, and the belief that great work is still fundamentally human. Our goal isn’t to ship the next feature. Each and every team of Notinos is working to set the standard for how humans work together in the AI era. From building a business’s system of record to making and managing AI agents to automating away the busy work, we care deeply about giving our customers more time for their life’s work. About the Role: We’re seeking an experienced UX Researcher to define and scale how we evaluate Notion’s AI-powered experiences—focusing on what “good” looks like not only for model output quality, but for the end-to-end product experience where people discover, set goals, delegate work, review results, and build trust over time with AI. This role sits at the intersection of research craft and evaluation operations: you’ll run studies that uncover user mental models, expectations, and failure/recovery behaviors, then translate those insights into reusable rubrics, workflows, and measurement approaches that product, design, engineering, and data science can apply consistently. This role can be based in either San Francisco or New York City. We work from our offices on Mondays, Tuesdays and Thursdays (our Anchor Days) because we do our best thinking and building together in person. We’re looking for someone who’s excited to work alongside the team during those days. What You'll Achieve: Define what “good” looks like (frameworks & rubrics): Establish clear, reusable evaluation criteria that reflect real user expectations—helpfulness,

Who We Are Notion is the collaborative AI workspace where teams and agents think together . We're building one place where your knowledge, projects, meetings, and AI tools live side by side, so work is faster, clearer, and less fragmented. Millions of individuals, small teams, and large companies run their work on Notion. Notinos (our employees) are customer zero in bringing this future of work to life. We care about craft, building things that last, and the belief that great work is still fundamentally human. Our goal isn’t to ship the next feature. Each and every team of Notinos is working to set the standard for how humans work together in the AI era. From building a business’s system of record to making and managing AI agents to automating away the busy work, we care deeply about giving our customers more time for their life’s work. About the Role: Notion is looking for an experienced engineer who has designed and built secure software systems to help define the security foundations for our AI products. You’ll work with product and engineering teams on agent runtimes, tool permissions, retrieval, content writes, observability, and abuse-resistant design. You’ll turn product risks into clear architecture, reusable guardrails, automated tests, and production systems that help teams ship new features safely. This role is based in San Francisco. We work from our offices on Mondays, Tuesdays and Thursdays (our Anchor Days) because we do our best thinking and building together in person. We’re looking for someone who’s excited to work alongside the team during those days. What You'll Achieve: Define and build security architecture for product surfaces that operate across customer workspace content, including tool execution, content writes, retrieval, permission checks, provenance, and auditability. Make the secure path the easy path for product teams by shipping reusable libraries, review patterns, test fixtures, and guardrails that prevent classes of vulnerabilities.

Who We Are Notion is the collaborative AI workspace where teams and agents think together . We're building one place where your knowledge, projects, meetings, and AI tools live side by side, so work is faster, clearer, and less fragmented. Millions of individuals, small teams, and large companies run their work on Notion. Notinos (our employees) are customer zero in bringing this future of work to life. We care about craft, building things that last, and the belief that great work is still fundamentally human. Our goal isn’t to ship the next feature. Each and every team of Notinos is working to set the standard for how humans work together in the AI era. From building a business’s system of record to making and managing AI agents to automating away the busy work, we care deeply about giving our customers more time for their life’s work. About the Role You’ll lead the Mobile AI engineering team, responsible for making Notion AI genuinely useful on phones and tablets. Mobile is where AI needs to work in the moment: when users are capturing ideas, catching up between meetings, asking questions, or trying to move work forward away from their desk. This role can be based in either San Francisco or New York City. We work from our offices on Mondays, Tuesdays and Thursdays (our Anchor Days) because we do our best thinking and building together in person. We’re looking for someone who’s excited to work alongside the team during those days. What You'll Achieve Define and evolve the roadmap for Notion’s core mobile AI surfaces, including chat, capture, agent workflows, workspace Q&A, and lightweight creation flows. Take new mobile AI ideas from exploration to shipped product, using prototypes, user feedback, and product data to decide what to build next. Improve the production quality of mobile AI by identifying instrumentation gaps, reliability risks, and performance bottlenecks before they become user problems. Help the team build the right technical foundations for fas

Who We Are Notion is the collaborative AI workspace where teams and agents think together . We're building one place where your knowledge, projects, meetings, and AI tools live side by side, so work is faster, clearer, and less fragmented. Millions of individuals, small teams, and large companies run their work on Notion. Notinos (our employees) are customer zero in bringing this future of work to life. We care about craft, building things that last, and the belief that great work is still fundamentally human. Our goal isn’t to ship the next feature. Each and every team of Notinos is working to set the standard for how humans work together in the AI era. From building a business’s system of record to making and managing AI agents to automating away the busy work, we care deeply about giving our customers more time for their life’s work. About The Role Build the most advanced AI Meeting Notes product — and expand it into broader “AI data capture” features that help teams turn conversations into durable context, tasks, and knowledge. Our mission is to 10x the rate of business context & data that enters Notion — optimized for agents — so teams get superhuman memory across workstreams and customers. Notion workspaces that use AI Meeting Notes already enter 6x more data on a daily basis, so we’re well on our way. What You'll Achieve Ship end-to-end product experiences across capture → transcript → summary → follow-ups (full-stack ownership). Make meeting & data capture feel effortless and magical (e.g., speaker identification via audio waveforms, richer in-meeting UX, smarter organization). Improve summary quality that teams trust: structure, factuality, and citations that make downstream agents and humans more capable. Raise the bar on reliability & observability across the pipeline (SLOs, debugging workflows, incident response) for realtime systems. Build agentic meeting workflows that turn discussions into tasks, follow-ups, and organized knowledge — so “w