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Job Requisition ID # 26WD101097 Autodesk Research – Intelligent Construction Summer 2027 | 12 weeks Position Overview Modern AI systems increasingly depend on their ability to access and use the right context at the right time. An important research challenge is how large, evolving bodies of information should be represented to support reliable inference. Autodesk Research provides a distinctive setting for this work. Construction projects are rich, complex information environments whose state changes continuously over time, making them a compelling domain for studying context and knowledge systems for AI. As a Research Intern, you will own a focused research problem in this area. You will investigate new approaches to building and retrieving structured context, develop experimental prototypes, and evaluate how effectively they support downstream AI reasoning. You will work closely with Autodesk researchers and engineers and have substantial freedom to bring ideas from your own research. Strong contributions may form the basis of an academic publication and future Autodesk research. Responsibilities • Conduct original research in context and knowledge systems for AI. Investigate methods for representing and retrieving information to support reliable contextual inference • Develop new approaches to context construction. Explore how relevant knowledge can be identified and assembled dynamically from large and evolving information environments • Build research prototypes. Implement experimental systems using graph-based

NVIDIA is seeking a Senior System Architect to define two foundational areas of the GPU: the mechanisms that manage GPU execution state and the register address and access architecture used across the processor. This hands-on role spans architecture, functional modeling, verification, hardware and software integration, and silicon bring-up. We collaborate across ASIC, firmware, driver, verification, and performance teams to guide features from early exploration through implementation and validation. The resulting architecture will build GPU responsiveness, reliability, scalability, software compatibility, and the way increasingly sophisticated processors are configured and managed. What you’ll be doing: Architect and evolve GPU context-management mechanisms, including efficient methods for saving and restoring execution state. Own the GPU-wide register address map, coordinate address allocation, resolve conflicts, and maintain a scalable architecture through multiple product iterations. Define requirements, interfaces, compatibility expectations, and on-die and cross-die interconnects for register access and programming. Develop C++ functional-model support and collaborate with hardware build, embedded software, device software, testing, and performance groups to translate architectural requirements into coordinated solutions. Evaluate tradeoffs across performance, area, complexity, scalability, reliability, compatibility, and development effort. Build validation strategies, debug cross-stack issues through pre-silicon validation and initial silicon testing, and improve the tools and automation supporting register-interface development. What we need to see: A bachelor’s degree in Computer Engineering, Computer Science, Electrical Engineering, or a similar field, or equivalent experience. 5+ years of proven experience in computer archit

Figma is growing our team of passionate creatives and builders on a mission to make design accessible to all. Figma’s platform helps teams bring ideas to life—whether you're brainstorming, creating a prototype, translating designs into code, or iterating with AI. From idea to product, Figma empowers teams to streamline workflows, move faster, and work together in real time from anywhere in the world. If you're excited to shape the future of design and collaboration, join us! We're looking for an experienced Design Leader to oversee our Context Platform Pillar, which homes several critical company initiatives including Design Systems, Code, MCP, CMS, Community, and more. Think of it as the team that drives the most important context for AI agents to help you design better products. In this role, you'll tackle strategic challenges from building new products to evolving and scaling existing ones - all while empowering your teams to deliver ambitious, high-quality work. If you're a leader who is especially deep in understanding modern AI + Design Systems workflows, and very passionate about empowering Designers through platform-wide investments in Figma's ecosystem, this role is for you. As a Design leader at Figma, you'll guide and grow a team of world-class designers, with the opportunity to expand this group as the scope and impact of our work evolves. In this deeply cross-functional role, you'll work in close collaboration with product management, engineering, research, marketing, and other teams to shape both product and business strategy in our next chapter. This is a full time role that can be held from one of our US hubs or remotely in the United States. What you'll do at Figma: Hire, manage, and develop a multi-team design group spanning Design Systems, Code, MCP, CMS, and Community Partner with Product and Engineering leads in this area to improve team processes and execution and coach individual teams through setting roadmap and strategy Develop a perspective

We're looking for an Engineering Manager to lead the Agent Context team in NYC. This team owns how Asana's AI systems search, retrieve, and reason over the work graph the search infrastructure, dense embedding pipelines, ranking systems, and evaluation frameworks that determine whether every AI experience at Asana is trustworthy or not. Your mission is to make retrieval comprehensive, reliable, and fast at enterprise scale, positioning Asana as the coordination and memory layer for the agentic enterprise. This is a high-leverage platform role: nearly every AI product at Asana - AI Teammates, chat experiences, agentic workflows depends on the systems this team builds. You will manage a team of senior engineers in New York collaborating daily with partner teams in San Francisco and Warsaw, and work alongside a dedicated Product Manager as your direct counterpart. This role is based in our New York office with an office-centric hybrid schedule. The standard in-office days are Monday, Tuesday, and Thursday; most Asanas have the option to work from home on Wednesdays. What you'll achieve Own the technical direction and delivery of Asana's retrieval stack end to end: lexical and semantic search, dense embedding generation and backfill at scale, chunking and ranking strategies, and RAG comprehensiveness across the work graph. Build and operate the evaluation infrastructure that makes retrieval quality measurable recall/precision benchmarks, offline and online evals, and comparative testing across retrieval backends - so quality decisions are made with data, not vibes. Drive the cost, performance, and quality tradeoffs that define this space: when semantic search earns its infrastructure cost over lexical, how to hit latency targets without sacrificing recall, and how retrieval improvements compound into cheaper, faster downstream LLM calls. Set and enforce the bar for how other teams at Asana integrate with retrieval: clear ownership of embedding decisions, rollout g

About the Team The Agent Post-Training team creates the frontier agents OpenAI ships to the world. We are training the models behind our agents in Codex, ChatGPT, the API, and other frontier products: persistent, proactive intelligence that can operate computers, collaborate with people and other agents, and expand what people and organizations can imagine, attempt, and achieve. We define what the next generation of agents should be able to do, build the training signal that teaches those abilities, and run the experiments that make them real. Our work spans coding, tool use, computer use, multi-agent coordination, long-horizon execution, factuality, instruction following, calibrated reasoning, and taste. Our team is where new model capabilities get made. We build the data, environments, graders, training methods, and feedback loops that shape what OpenAI's next agents can do, then carry those capabilities through major training runs and into the products people use. About the Role We believe that the final enabler for AGI is spending compute on context. As a Context Researcher on Agent Post-Training, you will scale compute spent on context. You will get to work in our frontier training stack on enabling the next paradigm of model training with a clear product interface for iterative deployment (Codex Chronicle). You will work with researchers, engineers, product teams, infrastructure teams, and safety/alignment partners to decide what should go into major model runs, measure whether it worked, and ship improvements into products used by real people. This is a high-agency role for people who want their work to land directly in frontier models. In this role, you might Design and run experiments that improve scaling of compute on context. Own end-to-end improvements to the post-training stack, including RL, data pipelines, graders, reward signals, evals, diagnostics, and model-behavior analysis. Build evals and environments that expose the next set of model failures,

About us Sierra is the leading platform for customer-facing AI agents, working with many of the world's biggest brands — including The GAP, Rocket Mortgage, SoFi, Sutter Health, and SoftBank — to transform how they serve customers and grow their businesses. We are primarily an in-person company based in San Francisco, with growing offices across North America, Europe, and Asia. We are guided by a set of values that are at the core of our actions and define our culture: Trust, Customer Obsession, Craftsmanship, Intensity, and a commitment to balancing Family along the way. These values are the foundation of our work, and we are committed to upholding them in everything we do. Our co-founders are Bret Taylor and Clay Bavor . Bret currently serves as Board Chair of OpenAI. Previously, he was co-CEO of Salesforce (which had acquired the company he founded, Quip) and CTO of Facebook. Bret was also one of Google's earliest product managers and co-creator of Google Maps. Before founding Sierra, Clay spent 18 years at Google, where he most recently led Google Labs. Earlier, he started and led Google’s AR/VR effort, Project Starline, and Google Lens. Before that, Clay led the product and design teams for Google Workspace. What you'll do You’ll join a full-stack data team building the systems making our AI agents measurably smarter with every interaction, building the real-time pipelines, analytics products, and deep personalization primitives that turn millions of conversations into business outcomes. You’ll work across these areas: Data Foundations: Architect and build our core platform to handle data at scale with low latency. This includes our real-time eventing infrastructure, streaming and batch ETL pipelines, and our Iceberg-based data lakehouse. You will own the systems for interactive OLAP querying, orchestration, and experimentation, ensuring our data is trustworthy, fast, and easy to use for the entire organization. Memory & Personalization: Power the next gene

We’re hiring a Senior Technical Product Marketing Manager to lead positioning, messaging, and product adoption across our AI and agentic context solutions. This is a high-impact role for a technical marketer who thinks and acts like a builder. Most AI systems don't fail because the model is bad—they fail because they lack a crucial, contextual foundation. MongoDB owns a piece of nearly every step in that chain. This role requires deep technical expertise across the context stack—including VoyageAI embedding and reranking models, MCP Server, and the coding agent ecosystem (Claude Code, Cursor, GitHub Copilot, Gemini CLI, Codex, etc.)—combined with product marketing instincts to deeply understand the market and translate technical depth into crisp, differentiated messaging for distinct user and buyer personas. The ideal candidate has experience building and shipping AI-enabled products and using developer tools in their day-to-day workflows. Individuals with prior experience in technical sales, developer relations, or software development are encouraged to apply. The ideal candidate is a voracious consumer of AI research and pays close attention to shifting patterns in how software and AI applications are built and consumed. This individual is confident in communicating with technical practitioners and non-technical decision makers in one-to-few and one-to-many engagements for internal and external audiences. You will leverage your technical depth to craft clear, compelling, and highly differentiated messaging by working backward from customer requirements. We are looking to speak to candidates who are based in Dublin for our hybrid working model. What You’ll Do Drive Strategy & Execution: Act as the strategic owner for MongoDB’s context engineering portfolio—MCP Server, Agent Skills, VoyageAI, and more— aligning roadmap and go-to-market with MongoDB’s long-term business goals, in collaboration with Product Management, Engineering, Developer Relations, Partn

About the team: Rubrik secures and accelerates the world’s AI transformation. As AI agents reshape the enterprise, Rubrik’s Enterprise AI Incubation team proves it on Rubrik itself. We are building a thinking enterprise: applications that don't just record the business but help run it. They learn from our data, act through our own agents, and improve with every decision. Fully backed by executive leadership, this team drives meaningful, large-scale enterprise transformation. About the role: We want senior engineers who have already shipped agents that real people rely on, and who are ready to do it again at higher stakes. You will drop into the real work, redesign it around agents that carry it end to end, and ship it as the new way that part of Rubrik operates.You’ll own your agent systems end to end: understanding the workflow, designing the architecture, writing the code, deploying, and running it in production. Rather than simply querying an API, you engineer robust, production-grade infrastructure around model endpoints, integrating custom tooling, context pipelines, automated evaluations, and defensive guardrails to ensure resilience against unstructured real-world data. You also decide whether a problem needs an agent, a simpler automation, or nothing at all, and you have explicit authority to stop or re-scope work that won’t deliver impact. You thrive in ambiguous environments with a low-ego mindset, leveraging AI coding tools as core collaborative partners in your engineering workflow. What you’ll do: Lead product discovery alongside Product Managers and domain experts to understand real workflows, map them out, and define clear problems, baselines, and success criteria as the foundation for building agentic solutions. Design, build, test, and deploy production agents, automations, and internal tools using coding agents, LLM APIs, and agent frameworks, integrated with Rubrik’s internal agent platform and business systems. Turn complex processes into multi-a

About PostHog PostHog is your product’s context layer. It ingests and stores your analytics, errors, replays, and business data so you and your agents can query and act on it. We launched out of Y Combinator's W20 cohort . We've since shipped more than a dozen products, including: A suite of analytics and observability tools, including product analytics , replay vision , AI observability , and error tracking PostHog MCP for users and their agents to query and act on their product and business data Data warehouse so users can query product and customer data together using custom SQL insights. We are: Product-led . More than 500K organizations have installed PostHog, mostly driven by word-of-mouth. We have intensely strong product-market fit. Default alive . Revenue is growing incredibly quickly, and we're very efficient. We raise money to push ambition and grow faster, not to keep the lights on. Well-funded. We've raised more than $180m from some of the world's top investors. We're set up for a long, ambitious journey. We're focused on building an awesome product for end users, hiring exceptional teammates, shipping fast, and being as weird as possible . Things we care about Transparency: Everyone can read about our roadmap, how we pay (or even let go of) people, our strategy, and how we work, in our public company handbook . Internally, we share revenue, notes and slides from board meetings, and fundraising plans, so everyone has the context they need to make good decisions. Autonomy: We don’t tell anyone what to do. Everyone chooses what to work on next based on what's going to have the biggest impact on our customers, and what they find interesting and motivating to work on. Engineers lead product teams and make product decisions . Teams are flexible and easy to change when needed. Shipping fast: Why not now? We want to build a lot of products; we can't do that shipping at a normal pace. We've built the company around small teams – autonomous, highly-efficient gro

About PostHog PostHog is your product’s context layer. It ingests and stores your analytics, errors, replays, and business data so you and your agents can query and act on it. We launched out of Y Combinator's W20 cohort . We've since shipped more than a dozen products, including: A suite of analytics and observability tools, including product analytics , replay vision , AI observability , and error tracking PostHog MCP for users and their agents to query and act on their product and business data Data warehouse (existing text is fine) We are: Product-led . More than 500K organizations have installed PostHog, mostly driven by word-of-mouth. We have intensely strong product-market fit. Default alive . Revenue is growing incredibly quickly, and we're very efficient. We raise money to push ambition and grow faster, not to keep the lights on. Well-funded. We've raised more than $180m from some of the world's top investors. We're set up for a long, ambitious journey. We're focused on building an awesome product for end users, hiring exceptional teammates, shipping fast, and being as weird as possible . Things we care about Transparency: Everyone can read about our roadmap, how we pay (or even let go of) people, our strategy, and how we work, in our public company handbook . Internally, we share revenue, notes and slides from board meetings, and fundraising plans, so everyone has the context they need to make good decisions. Autonomy: We don’t tell anyone what to do. Everyone chooses what to work on next based on what's going to have the biggest impact on our customers, and what they find interesting and motivating to work on. Engineers lead product teams and make product decisions . Teams are flexible and easy to change when needed. Shipping fast: Why not now? We want to build a lot of products; we can't do that shipping at a normal pace. We've built the company around small teams – autonomous, highly-efficient groups of cracked engineers who can outship much larger comp

About PostHog PostHog is your product’s context layer. It ingests and stores your analytics, errors, replays, and business data so you and your agents can query and act on it. We launched out of Y Combinator's W20 cohort . We've since shipped more than a dozen products, including: A suite of analytics and observability tools, including product analytics , replay vision , AI observability , and error tracking PostHog MCP for users and their agents to query and act on their product and business data Data warehouse so users can query product and customer data together using custom SQL insights. We are: Product-led . More than 500K organizations have installed PostHog, mostly driven by word-of-mouth. We have intensely strong product-market fit. Default alive . Revenue is growing incredibly quickly, and we're very efficient. We raise money to push ambition and grow faster, not to keep the lights on. Well-funded. We've raised more than $180m from some of the world's top investors. We're set up for a long, ambitious journey. We're focused on building an awesome product for end users, hiring exceptional teammates, shipping fast, and being as weird as possible . Things we care about Transparency: Everyone can read about our roadmap, how we pay (or even let go of) people, our strategy, and how we work, in our public company handbook . Internally, we share revenue, notes and slides from board meetings, and fundraising plans, so everyone has the context they need to make good decisions. Autonomy: We don’t tell anyone what to do. Everyone chooses what to work on next based on what's going to have the biggest impact on our customers, and what they find interesting and motivating to work on. Engineers lead product teams and make product decisions . Teams are flexible and easy to change when needed. Shipping fast: Why not now? We want to build a lot of products; we can't do that shipping at a normal pace. We've built the company around small teams – autonomous, highly-efficient gro

About PostHog PostHog is your product’s context layer. It ingests and stores your analytics, errors, replays, and business data so you and your agents can query and act on it. We launched out of Y Combinator's W20 cohort . We've since shipped more than a dozen products, including: A suite of analytics and observability tools, including product analytics , replay vision , AI observability , and error tracking PostHog MCP for users and their agents to query and act on their product and business data Data warehouse so users can query product and customer data together using custom SQL insights. We are: Product-led . More than 500K organizations have installed PostHog, mostly driven by word-of-mouth. We have intensely strong product-market fit. Default alive . Revenue is growing incredibly quickly, and we're very efficient. We raise money to push ambition and grow faster, not to keep the lights on. Well-funded. We've raised more than $180m from some of the world's top investors. We're set up for a long, ambitious journey. We're focused on building an awesome product for end users, hiring exceptional teammates, shipping fast, and being as weird as possible . Things we care about Transparency: Everyone can read about our roadmap, how we pay (or even let go of) people, our strategy, and how we work, in our public company handbook . Internally, we share revenue, notes and slides from board meetings, and fundraising plans, so everyone has the context they need to make good decisions. Autonomy: We don’t tell anyone what to do. Everyone chooses what to work on next based on what's going to have the biggest impact on our customers, and what they find interesting and motivating to work on. Engineers lead product teams and make product decisions . Teams are flexible and easy to change when needed. Shipping fast: Why not now? We want to build a lot of products; we can't do that shipping at a normal pace. We've built the company around small teams – autonomous, highly-efficient gro

Do work that matters. At AlertMedia, we help organizations protect their people, operations, and brand. Our modern Risk Intelligence and Response platform empowers teams to detect emerging threats, assess impact, and respond with confidence. We believe building resilience should be simpler—and it starts with bringing critical information and workflows together in one unified platform. Our core values drive us in our important mission of keeping people safe & informed: We’re humans not robots Customers always come first We work better together Simplicity is our strength Our reputation is priceless Hard work pays off As one of the fastest-growing software companies in the country, AlertMedia is looking for a Sr. Software Engineer with full-stack experience. This role is on our AI Agent and Orchestration team, building the AI Assistant and Orchestration products and the agents and platform capabilities that power them. As an AI-forward company, we actively use modern AI tools such as Claude, Codex, and other emerging technologies to help our engineers work smarter, move faster, and build better products. Who you are: You thrive in a collaborative engineering environment that plays to everyone's strengths with a willingness to work across the entire stack. You’ve developed scalable production web applications in Python/Django/Next.js/React . You understand how LLM applications work — context, tool calling, evaluation, and the ways they fail. You care about the quality of your work, the impactful product you help build, and the team you help build it with. You have AWS (or other cloud) experience and are willing to learn from people with both more and less experience than you. You are a user of AI-assisted development tools that improve engineering workflows, code quality, and team productivity. What you get to do every day: Build and ship features

About PostHog PostHog is your product’s context layer. It ingests and stores your analytics, errors, replays, and business data so you and your agents can query and act on it. We launched out of Y Combinator's W20 cohort . We've since shipped more than a dozen products, including: A suite of analytics and observability tools, including product analytics , replay vision , AI observability , and error tracking PostHog MCP for users and their agents to query and act on their product and business data Data warehouse so users can query product and customer data together using custom SQL insights. We are: Product-led . More than 500K organizations have installed PostHog, mostly driven by word-of-mouth. We have intensely strong product-market fit. Default alive . Revenue is growing incredibly quickly, and we're very efficient. We raise money to push ambition and grow faster, not to keep the lights on. Well-funded. We've raised more than $180m from some of the world's top investors. We're set up for a long, ambitious journey. We're focused on building an awesome product for end users, hiring exceptional teammates, shipping fast, and being as weird as possible . Things we care about Transparency: Everyone can read about our roadmap, how we pay (or even let go of) people, our strategy, and how we work, in our public company handbook . Internally, we share revenue, notes and slides from board meetings, and fundraising plans, so everyone has the context they need to make good decisions. Autonomy: We don’t tell anyone what to do. Everyone chooses what to work on next based on what's going to have the biggest impact on our customers, and what they find interesting and motivating to work on. Engineers lead product teams and make product decisions . Teams are flexible and easy to change when needed. Shipping fast: Why not now? We want to build a lot of products; we can't do that shipping at a normal pace. We've built the company around small teams – autonomous, highly-efficient gro