Software Engineer, Staff: Applied AI, Science & Engineering

Perplexity is looking for an Applied AI Engineer to design, build, and iterate on cutting-edge agents powering our core experience in Perplexity Computer. Working in this mission critical team, you will develop frontier context layer applications - fulfilling the curiosity of millions of users across the globe. Key Responsibilities Apply state-of-the-art ML and LLM techniques to solve problems spanning: Personalization (LLM memory, context summarization, retrieval and ranking); Contextual recommendations and Monetization applications Build frontier agent capabilities on top of Perplexity Computer Build auto research harness for both offline and online techniques, designing experiments and metrics that provide deep insight into quality and impact. Own the entire model lifecycle from research to production: data analysis, modeling, evaluation, offline/online A/B testing, and iterative improvement and build autonomous harness for agent squad to explore different problem spaces. Collaborate cross-functionally with engineers, PMs, data scientists, and designers to ensure our AI drives meaningful product improvements. Stay at the forefront of ML/AI innovation by evaluating and incorporating emerging research and algorithms into the product lifecycle. Preferred Qualifications 5+ years experience building and shipping robust AI products for large-scale, user-facing or data-driven products. Strong software engineering skills (Python, production-quality codebases, collaborative development) and experience using agentic coding tools for large scale parallel developments. In-depth experience with the full AI lifecycle: data analysis, rigorous evaluation, and ongoing monitoring/improvement. Proven collaborator and communicator; excels in high-velocity, cross-functional teams. Curious, driven by end-user/product impact, and passionate about advancing the state of applied ML and AI. BS, MS, or PhD in Computer Science, Engineering, or related field (or equivalent experience). Bonus

About the Team Consumer Monetization builds the experiences and systems that power how customers purchase and pay for OpenAI products. Our scope spans purchasing flows, payments, subscriptions, and billing, along with the shared capabilities that support new products, offers, and distribution channels. We own both customer-facing experiences and the underlying platforms that power them. We partner closely with Product, Design, Growth, Data Science, and engineering teams across OpenAI to make purchasing effective and reliable, and new offerings easier to launch and monetize. About the Role We’re looking for experienced Staff+ engineers to evolve the payments, billing, and subscription capabilities that support OpenAI’s growing product portfolio. You’ll tackle problems where correctness, reliability, and flexibility are essential: supporting new billing requirements, managing the billing lifecycle, synchronizing state across internal systems and external providers, and enabling new products and commercial models. Your work may span several areas based on your expertise and team priorities: Billing and monetization capabilities: Extend billing capabilities and improve integrations and state consistency across systems to support new products and business models. Subscriptions: Orchestrate purchases, renewals, plan changes, cancellations, and recovery, ensuring customers are charged correctly and receive the right benefits. Payments: Expand payment capabilities through processor integrations, routing, and broader payment-method coverage. Risk and integrity: Partner with risk and integrity teams to integrate controls into purchasing flows, reducing abuse while protecting legitimate customer experiences. You’ll help set technical direction while remaining hands-on in implementation and delivery. This is an opportunity to solve complex engineering problems at scale, connect architecture decisions to customer and business outcomes, and help other engineers take on broader ow

About the Team Consumer Monetization builds the experiences and systems that power how customers purchase and pay for OpenAI products. Our scope spans purchasing flows, payments, subscriptions, and billing, along with the shared capabilities that support new products, offers, and distribution channels. We own both customer-facing experiences and the underlying platforms that power them. We partner closely with Product, Design, Growth, Data Science, and engineering teams across OpenAI to make purchasing effective and reliable, and new offerings easier to launch and monetize. About the Role We’re looking for experienced Staff+ full-stack engineers to shape purchasing experiences and monetization capabilities across OpenAI products. You’ll work across web experiences, product APIs, and shared components, combining strong product judgment with technical depth. The work ranges from improving checkout conversion and performance to enabling new pricing models, offers, and ways for customers to purchase our products. You’ll help identify opportunities, turn ambiguous goals into concrete technical plans, and lead initiatives from exploration through launch. As patterns emerge across products, you’ll develop reusable capabilities that make future launches faster and more consistent. This is a hands-on technical leadership role with substantial ownership over architecture, implementation, and product outcomes. This role is based in San Francisco, with three days per week in the office. In this role, you will: Architect and build purchasing experiences end to end, from frontend interactions through the product APIs and backend integrations that support them. Improve checkout conversion, performance, and reliability through experimentation, product analytics, and customer insights. Develop shared checkout components and monetization capabilities that support new products, pricing models, offers, and distribution channels. Partner with Product, Design, Growth, and Data Science to

About the Team Consumer Monetization builds the experiences and systems that power how customers purchase and pay for OpenAI products. Our scope spans purchasing flows, payments, subscriptions, and billing, along with the shared capabilities that support new products, offers, and distribution channels. We own both customer-facing experiences and the underlying platforms that power them. We partner closely with Product, Design, Growth, Data Science, and engineering teams across OpenAI to make purchasing effective and reliable, and new offerings easier to launch and monetize. About the Role We’re looking for experienced Staff+ engineers with deep iOS or Android expertise and demonstrated experience contributing beyond mobile to frontend web or backend development. You’ll shape and build purchasing and subscription experiences across mobile applications, web, and supporting product APIs. The work spans improving conversion, performance, and reliability, building reusable components, and enabling new product launches. You’ll combine product judgment with technical depth to set direction, lead initiatives across teams, and remain hands-on through implementation and delivery. Approximately 50% of the work will initially be native mobile development, with the remainder across web and product APIs. We’re looking for engineers who enjoy working across the stack and have concrete examples of doing so professionally. Depth in either iOS or Android is required; experience in both is not required. This role is based in San Francisco, with three days per week in the office. In this role, you will: Architect and build purchasing and subscription experiences across native mobile, mobile web, and supporting product APIs. Partner with Product, Design, and Growth to identify customer needs, prioritize improvements, and shape technical direction for purchasing experiences. Improve conversion, performance, and reliability through experimentation, product analytics, and customer insights

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. We are hiring a Staff Software Engineer for our Frontier Security AI team. Snowflake's Frontier Security AI teams develop production-grade LLM applications, intelligent agents, AI infrastructure, and evaluation systems for enterprise customers — products that must meet a high bar for quality, security, reliability, and efficiency while operating over sensitive data at large scale. In this role, you will lead the design and development of our Agentic Harness and agent evaluation platform, working across product, infrastructure, applied AI, security, and modeling teams to take new capabilities from prototype to dependable customer value. AS A STAFF SOFTWARE ENGINEER AT SNOWFLAKE, YOU WILL: Architect and build the Agentic Harness that executes complex, multi-step AI workflows across models, tools, data, and services. Design stable interfaces for tool execution, context construction, state management, memory, permissions, retries, fallbacks, and human review. Own agent quality end to end by building evaluation harnesses, representative datasets, automated graders, experiment pipelines, and release gates. Convert ambiguous reports such as "the agent feels worse" into measurable failure modes, reproducible tests, and durable fixes. Analyze production agent trajectories to identif

The ML Observability team builds cutting-edge tools to monitor, explain, and improve AI systems in production, particularly those leveraging Large Language Models (LLMs) and generative AI. We provide robust, scalable observability for AI workloads, including drift detection and model evaluation, and behavior tracing, enabling customers to ship AI with confidence. As a Staff Engineer, you’ll lead the development of new features and foundational capabilities within Datadog’s LLM Observability product. You will shape product direction, drive experimentation, and apply your deep understanding of both AI systems and software engineering to solve open-ended problems in the fast-moving AI landscape. Your work will directly impact how our customers monitor, troubleshoot, and optimize LLM-based applications in production. Join us in building the foundational tools that make AI systems observable, understandable, and reliable in the real world. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Drive design and implementation of LLM observability features. Ideate, prototype, and scale new product features to provide insights and drive improvements for generative AI systems Work cross-functionally with other eng teams, product, UX, and applied science to iterate fast and find product-market fit Develop and extend tools for tracing, evaluating, and debugging LLMs Influence architecture decisions and mentor engineers to build resilient, high-performance systems Stay close to customer pain points and use those insights to guide product and engineering priorities Stay current with industry trends and advancements in machine learning and observability, driving innovation within the team Who You Are: You have a BS/MS/PhD in a Computer Science, Engineering or r