Applied Ai Architects Manager Jobs

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . Pinterest is where more than half a billion people come to find what they love and build a life around it. That experience depends on deep understanding — understanding what a Pinner loves, what a Pin means, and how to surface the right content at the right moment. Across recommender systems, signals, and representation learning, the Applied Sciences team develops the next generation technologies that power personalized discovery across Pinterest. We’re looking for Staff Product Managers to help shape the next chapter of Pinterest’s applied AI/ML platform. In these roles, you’ll bring together research ambition and product discipline to help define the future of personalized experiences at one of the world’s leading discovery platforms. The roles Applied Sciences at Pinterest spans core areas including representation learning, signals, and recom

Overview: Guidepoint is investing in applied AI across its research platform. We're building conversational AI systems that interact with our global expert network at scale — combining real-time voice, LLM-driven orchestration, and retrieval over large proprietary datasets. You'll be an early engineer on a new initiative: taking working prototypes to production and shaping the architecture as the product scope grows. This is a hands-on role with broad ownership, close to product and leadership. This role is hybrid in our Toronto Office What You'll Do: Real-time conversational AI: voice- and chat-based agents with low-latency requirements, built on modern telephony and real-time media infrastructure. LLM orchestration: agentic systems that pursue goals over multi-turn conversations, with hard behavioral guarantees enforced in code — not just prompts. Multi-channel session management: stateful user interactions that move seamlessly across channels. Retrieval and grounding: connecting LLM systems to large internal knowledge assets, with structured data flowing back. Evaluation infrastructure: measuring conversational quality against human baselines and gating rollouts on metrics, not vibes. Own services end-to-end: design, implementation, deployment (Kubernetes/Azure), and operations, including latency-sensitive real-time workloads. Design and tune LLM pipelines: context engineering, structured outputs, model selection, cost/latency tradeoffs across vendors. Build the eval loop and treat quality as a number: define metrics, run experiments, gate releases on them. Integrate third-party AI and voice vendors behind clean abstractions so providers stay swappable. Partner with product and compliance stakeholders to encode domain rules into the system. Set engineering patterns for a growing team: code review, observability, incident habits. What You Have: 6+ years of software engineering, with 2+ years building LLM-powered products in production (not notebooks): orchestratio

The team + the role Pendo's Applied AI team turns AI infrastructure into real business outcomes across Sales, Marketing, and Customer Engineering. AI here isn't a feature we bolt on — it's how we scale GTM capability across the company. We build AI that makes GTM teams measurably faster and more effective, and we measure success by whether those teams are actually using what we ship and getting real value from it. As an Applied AI Engineer, you'll own the full lifecycle of AI-powered solutions — from problem definition and prompt design through to production deployment and ongoing iteration. You'll work directly with GTM stakeholders to identify high-value problems, set realistic expectations about what AI can and can't do, and ship solutions that stick. The best person for this role has a strong engineering instinct, deep curiosity about how businesses operate, and the judgment to know when AI is the right tool — and when it isn't. This role is based in Raleigh, NC and follows Pendo's hybrid model: in-office 3 days per week. What this looks like day-to-day Own AI solutions end-to-end: problem definition, prompt design, production deployment, monitoring, and iteration — you ship, you watch, you improve. Build and manage GTM workflow automations that reduce manual work across Sales, Marketing, and Customer Engineering systems, including Slackbots and other integrations. Partner directly with GTM stakeholders to surface high-value problems, validate solutions, drive adoption, and set honest expectations about AI capabilities and limitations. Develop and maintain prompt management practices that make AI outputs reliable, auditable, and improvable over time — treat prompts as production code, not experiments. Work with the Data Platform and Systems teams to identify foundational tooling gaps and contribute clear, actionable requirements based on what you encounter in production. Share reusable AI workflow patterns and tool findings with the broader team — your impact sh

AI Teammates are Asana’s flagship AI innovation - autonomous agents embedded directly into enterprise workflows that reason, act, and proactively drive work forward. The AI Teammates Platform (AITP) team owns the execution engine and platform layer that makes these AI Teammates effective, reliable, and scalable. We build the core systems behind agentic execution: model evaluation and rollouts, proactive detection of blocked work, execution quality infrastructure, tool orchestration, and the platform APIs that power AI across all of Asana engineering. Rather than building a monolithic feature, we build a composable foundation. If a Teammate reasons, acts, or autonomously improves - that’s us. We’re looking for an experienced Staff Software Engineer to drive the technical strategy, architecture, and execution for the AI Teammates Platform. You will bridge the gap between frontier AI capability and enterprise-grade software engineering, operating in close partnership with frontier model providers while building systems that scale to millions of users. If you are passionate about applied AI, agentic orchestration, high-reliability backend systems, and growing high-performing engineering teams, we’d love to hear from you! This role is based in our San Francisco 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. Working from home on Fridays depends on the type of work you do and the teams with which you partner. If you're interviewing for this role, your recruiter will share more about the in-office requirements. What You’ll Achieve Set the technical strategy for the AI Teammates execution engine, tool orchestration, and platform APIs within Asana, advocating for engineering-driven investments with a vision for keeping our systems flexible, reliable, and maintainable to meet customer needs now and in the future Drive the team to continually and hol

AI Teammates are Asana’s flagship AI innovation - autonomous agents embedded directly into enterprise workflows that reason, act, and proactively drive work forward. The AI Teammates Platform (AITP) team owns the execution engine and platform layer that makes these AI Teammates effective, reliable, and scalable. We build the core systems behind agentic execution: model evaluation and rollouts, proactive detection of blocked work, execution quality infrastructure, tool orchestration, and the platform APIs that power AI across all of Asana engineering. Rather than building a monolithic feature, we build a composable foundation. If a Teammate reasons, acts, or autonomously improves - that’s us. We’re looking for an experienced Technical Lead to drive the technical strategy, architecture, and execution for the AI Teammates Platform. You will bridge the gap between frontier AI capability and enterprise-grade software engineering, operating in close partnership with frontier model providers while building systems that scale to millions of users. If you are passionate about applied AI, agentic orchestration, high-reliability backend systems, and growing high-performing engineering teams, we’d love to hear from you! This role is based in our San Francisco 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. Working from home on Fridays depends on the type of work you do and the teams with which you partner. If you're interviewing for this role, your recruiter will share more about the in-office requirements. What You’ll Achieve Set the technical strategy for the AI Teammates execution engine, tool orchestration, and platform APIs within Asana, advocating for engineering-driven investments with a vision for keeping our systems flexible, reliable, and maintainable to meet customer needs now and in the future Drive the team to continually and holistically

Who We Are Artefact is an applied AI company. We build systems that run in production, in our clients' own cloud, and keep running after we leave. 2,500+ people across 27 countries and 1,000 clients, including some of the largest consumer brands in the world. Not a strategy house that discovered AI eighteen months ago, and not a prototype shop that hands you something you will rebuild from scratch. Three ingredients make that possible, and very few firms have all three: the data, real and messy and at enterprise scale; an applied AI team that can put a model into a governed production environment; and the transformation muscle to make people actually use it. Agentic AI lands on marketing before it lands anywhere else. Agents browse, compare and buy; clicks stop meaning what they meant; the shelf turns into an API. Every senior marketing and commerce leader we talk to is asking the same two questions — am I still visible, and can I still prove what worked — and almost nobody can answer them. The Role We are hiring a Director to lead marketing measurement and effectiveness for our US client portfolio, starting with a large, in-flight measurement program for a major US financial services client. This is a player-coach role. You will own the methodology and the client relationship, lead a multi-workstream data science team, and stay close enough to the models to challenge assumptions, review code and unblock hard technical problems yourself. You will also help us productize what we build — turning measurement work into reusable accelerators and points of view that scale across accounts. You should be able to step into a live, complex measurement program quickly and earn credibility with senior client stakeholders in the first weeks, not the first quarter. What You'll Do You will own the hardest question in marketing: what actually caused the sales. Marketing Mix Modeling, incrementality testing, geo-lift, attribution — for a brand where a few points of budget reallocati

About Meesho Meesho is India's fastest-growing internet commerce company, on a mission to democratize e-commerce for everyone. We serve millions of customers and over 1.75 million sellers through technology-driven innovation, building the scalable systems that power Meesho's most critical surfaces — Search, Recommendations, Personalized Ranking, Logistics, Fraud Detection, and Image Match. The AI Platform sits at the heart of this. It serves a peak of 1M+ real-time deep-learning model inferences per second on ordinary days, scaling 3x+ on sale days — with the reliability that scale demands. The team works at the frontier of applied AI and infrastructure — multi-region inference, novel embedding-search algorithms, and optimized open-weight LLM models — squeezing out every bit of computation and passing the cost savings straight back to customers. About the Role We are looking for an experienced Engineering Manager – AI Engineering to lead the development of scalable AI platforms and infrastructure while managing high-performing engineering teams. You will drive the design, delivery, and optimization of production-grade AI systems powering AI use cases across Meesho. What You'll Do Lead, mentor, and grow a team of AI engineers — setting technical direction, raising the engineering bar, and owning execution and delivery end to end. Architect and scale Meesho's AI platform: cross-region model inference, multi-GPU fleet allocation and management, distributed training, and feature-engineering infrastructure. Drive inference optimization across the full stack — GPU kernel tuning, quantization (including outlier/tail-distribution handling), and memory/IO-bandwidth optimization — while building agents that codify and delegate known optimization procedures. Optimize open-weight models at both the model and inference-engine level — distillation, quantization, speculative decoding, KV-cache and serving-engin

The Team + The Role Our Engineering Team is focused on building AI Products for our product experience (PX) platform. We build from the ground up to explore, prototype, and ship AI-native experiences that change how software teams understand and serve their users. This is not an AI layer added to existing product; it is a deliberate bet on what product intelligence looks like next. The team operates with high autonomy, moves quickly, and builds products without clear precedents. As a Sr. Software Engineer (AI), you will sit at the intersection of deep technical capability and strong product judgment. You will design and ship applied AI systems, including RAG pipelines, agentic workflows, and LLM-powered features, from prototype through production. You will make principled technical decisions, evaluate model behavior rigorously, and communicate tradeoffs clearly to engineers and non-engineers alike. This role is based in our New York office. What this looks like day-to-day Applied AI systems: Design and build AI systems including RAG pipelines, agentic workflows, and LLM-powered features. You will take work from prototype through production and ensure it can hold up in real customer environments. Technical decision-making: Make principled decisions on when to prompt, when to fine-tune, and when to use a different tool entirely. You will explain these tradeoffs clearly so the team can move quickly without sacrificing quality. Model evaluation: Instrument and evaluate model outputs rigorously by defining evaluation frameworks and catching hallucinations early. You will implement guardrails that can withstand real-world load and production use. Productionize AI ownership: Own model deployment, monitoring, latency optimization, cost management, and reliability at scale. You will help ensure AI systems are observable, efficient, and dependable in production. Full-stack product shipping: Contribute across the stack when needed because this team ships products, not just mod

Everpure (NYSE: P) has evolved from storage pioneer to data platform, closing fiscal 2026 with $3.7 billion in revenue, its first billion-dollar quarter, and accelerating growth into FY27. Our strategic agenda spans the companies defining the next era of technology - hyperscalers, AI labs, the AI hardware supply chain, data platform providers, and the broader AI ecosystem. This type of work—work that changes the world—is what the tech industry was founded on. So, if you're ready to seize the endless opportunities and leave your mark, come join us. THE ROLE Everpure is moving from an application-centric world to a data-centric one — where AI depends on trusted, well-governed, and contextualized data across the business. As part of this shift, we're looking for a Staff Analyst, AI & Automation to lead the technical build of AI and applied ML capability inside the analytics function. This is an individual contributor role — you will not manage people. Your leverage comes from what you build and ship: AI agents, applied ML models, and automated analytics workflows that change how insight gets produced, working closely with cross-functional teams to bring these to life. AI is changing by the week, not by the year. We're not looking for someone who adopts AI once it's already mainstream — we want someone who is naturally ahead of the curve: scanning what's new, testing it quickly, and bringing it into the team before it's obvious to everyone else. This role has real freedom to experiment, rethink existing approaches, and change course as the field moves. WHAT YOU'LL DO Own the technical build of AI-powered analytics tools — including RAG pipelines, LLM-assisted querying, agent workflows, and applied ML models. Our current stack includes Glean, Gemini, Claude Code and Snowflake Cortex, and we expect that to change; we care more that you pick up new tools quickly than that you already know ours. Apply data science methods (forecasting, segmentation, anomaly detection, c

Principal AI Research Scientist, Research Director - AI Scaling P-1227 About Databricks AI At Databricks, we are obsessed with enabling data teams to solve the world’s toughest problems, from security threat detection to cancer drug development, by building and running the world’s best data and AI platform. The Databricks AI Research organization enables companies to develop AI models and agents using their own data, with technologies ranging from post-training open source LLMs to developing advanced multi-agent architectures. Databricks AI is committed to the belief that a company’s AI models and agents are just as valuable as any other core IP, and that high-quality AI should be available to all. About the Scaling Research Team The Databricks AI Scaling team focuses on pushing the boundaries of large language model (LLM) training and inference efficiency beyond what is required to support existing models. The team explores novel avenues for scaling and efficiency improvements across algorithms, systems, and infrastructure, requiring researchers who can both drive independent research agendas and dive deep into low‑level implementation details with engineering partners. Role Summary As a Principal Research Scientist – AI Scaling, you will lead a team of world‑class researchers and engineers to advance the state of the art in large‑scale machine learning, focusing on post-training, RL and inference efficiency, optimization, and scaling. You will define and execute a research roadmap that advances the Databricks AI platform and delivers tangible improvements to how customers train, serve, and adapt LLMs at scale, working closely with product, data, and engineering leaders to bring cutting‑edge methods into production. The Impact You Will Have Lead and grow a multidisciplinary research team focused on foundational and applied AI problems, with a particular emphasis on LLM scaling, efficiency, and systems performance. Define the scaling research roadmap in alignment wi

Our Company Changing the world through digital experiences is what Adobe's all about. We empower people to create, collaborate, and deliver exceptional experiences—and our operations teams play a critical role in making that possible at scale. The Opportunity The Creativity & Productivity (C&P) Operations team is seeking an Operations AI Developer to advance operational excellence using applied AI. This role combines operations, automation, and emerging AI capabilities. It focuses on identifying, designing, building, and deploying intelligent solutions to improve efficiency, scalability, and decision-making across the organization. This position is just beginning — you will help set the course, not only follow it. Your main focus will be building internal tools that simplify how the C&P Operations organization operates. You will be finding opportunities to boost efficiency in workflows and connecting with a wider executive network that is being developed. The solutions made here may grow beyond C&P and reach across Adobe, so the quality, maintainability, and care in your work matter greatly. Comfort with unclear situations and the skill to build frameworks from nothing are crucial. You will be part of the Product Operations organization that reports into the Office of the President of C&P. You will work and collaborate closely with C&P Operations Leaders, engineering, and the Adobe Technical Systems (ATS) team. Your role is to convert real business needs into practical, scalable solutions. This is a high-visibility, hands-on role where you can influence how AI is adopted and expanded not only within C&P but possibly across Adobe. What You'll Do Identify and prioritize high-impact opportunities to apply AI and other tooling across C&P Operations workflows and processes Design, develop, and roll out AI agents, copilots, and

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

About the Role Together AI is building the AI Native Cloud — an end-to-end platform for generative AI lifecycle, integrating fast, reliable inference, and model-shaping services with cutting-edge AI cloud infrastructure. We are looking for a seasoned Senior Technical Recruiter to partner closely with AI Research and Engineering leadership to scale world-class research teams across kernels, inference optimization, applied AI and model shaping. This role is ideal for someone who understands the unique dynamics of recruiting top-tier AI researchers and research engineers in a highly competitive market and can operate as a strategic talent partner to technical leadership. Responsibilities Partner with executives, research leadership, and hiring managers to define and execute hiring strategies Lead full-cycle recruiting for specialized AI talent, including researchers, research engineers, applied scientists, and ML systems engineers Build and nurture relationships with top AI talent across academia, open-source communities, research labs, and industry networks Drive exceptional candidate experiences from initial engagement through offer close, with a strong focus on relationship building and long-term talent cultivation Provide market intelligence on AI talent trends, compensation, competitive hiring landscapes, and emerging research organizations to influence hiring strategy and organizational planning Collaborate cross-functionally with sourcing, coordination, people operations, and leadership teams to continuously improve recruiting processes and operational excellence Design and refine interview processes tailored for research hiring, including technical evaluations, publication reviews, and research presentation loops Requirements 5+ years of technical recruiting experience at high-growth technology companies, with a proven track record hiring exceptional AI researchers, research engineers, applied scientists, or ML infrastructure talent at leading AI labs, hyper-sc

Everpure (NYSE: P) has evolved from storage pioneer to data platform, closing fiscal 2026 with $3.7 billion in revenue, its first billion-dollar quarter, and accelerating growth into FY27. Our strategic agenda spans the companies defining the next era of technology - hyperscalers, AI labs, the AI hardware supply chain, data platform providers, and the broader AI ecosystem. This type of work—work that changes the world—is what the tech industry was founded on. So, if you're ready to seize the endless opportunities and leave your mark, come join us. THE ROLE Our Senior Applied AI Engineer builds and operate production-grade AI systems that extract meaning from large-scale unstructured document collections, enabling enterprise data discovery classification, and governance. This role owns the full lifecycle of graph intelligence solutions — from problem definition and data modelling, to building and enriching knowledge graphs, and deploying ML- and LLM-assisted analytics in production. The focus is on semantic and contextual analysis of unstructured data to uncover relationships, patterns, and insights that support AI safety, security, and compliance requirements. WHAT YOU'LL DO Design, build, and deploy graph-based AI solutions, combining knowledge graphs , LLMs, and ML models applied to large-scale unstructured data Define and own data pipelines that extract, transform, and enrich entity relationships into production-grade knowledge graphs Integrate LLMs and ML models into text processing pipelines for classification, embedding generation, document similarity, and semantic analysis Design, deploy, and operate graph and vector databases to support retrieval, reasoning, and analytics Optimize models and inference pipelines for production constraints including latency, throughput, cost, and infrastructure Deploy, monitor, and iterate on ML systems in production environments ensuring reliability and continuous integration Drive architectural decisions and tech

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