Applied Ai Architects Manager Jobs

AI Platform builds the foundations of Datadog's AI efforts. The org is 70+ people organised in three pillars: training and serving (GPU clusters, distributed training, low-level infrastructure), agents (agent harnesses, memory systems, the internal AI gateway that routes every LLM request at Datadog), and evaluation and experimentation. This role sits in the evaluation and experimentation pillar, which owns Datadog's shared annotation and evaluation infrastructure — including the evaluation scenario store and the telemetry archival systems used across the Bits org. Together they let an agent travel back in time and query what Datadog looked like at the exact moment an incident happened, so scenarios can be replayed and agent performance tracked over time. Specifically, you'll be the first applied scientist on GenSim (Generative Simulations), the team that builds the environments Datadog's agents learn in. GenSim doesn't replay sampled telemetry — it stands up real, fully instrumented applications that talk to Datadog, drives them with representative traffic, injects controlled failures, and records what happens. Because GenSim injected the failure, it knows the ground truth. That corpus — hundreds of postmortem-derived scenarios and thousands of runnable applications — is today the primary source of post-training data for Datadog's own SRE model, and the substrate that Bits AI SRE and our other agents are trained and evaluated against. The team has no applied science support today and is learning post-training data methodology on the fly. That's the gap this role fills, and the open questions are the interesting part. How do you tell whether a generated environment is actually representative of the messy, incomplete telemetry real customers run — rather than a suspiciously clean one where every monitor exists and every service emits complete logs? How do you make injected problems genuinely hard, and how do you even measure difficulty? How do you define and control

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 applied scientists with a Machine Learning and Artificial Intelligence background to build AI technologies and make Figma products more magical.. You will be driving fundamental and applied research in this area. You will be combining industry best practices and a first-principles approach to design and build AI/ML models and systems to improve Figma’s products. 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: You will be driving fundamental and applied research in AI. You will explore the boundaries of what is possible with the current technology set to build best in class models for Figma’s domains You will be combining industry best practices and a first-principles approach to build cutting edge Generative AI models, using techniques like Supervised Finetuning (SFT), Reinforcement Learning (RL), prompt improvements and synthetic data generation Work in concert with product and infrastructure engineers to improve Figma’s products through AI powered features Collaborate closely with product managers and engineers to transform user feedback into requirements for AI systems Build evaluation systems to measure and improve quality of AI features in Figma products We'd love to hear from you if you have: Extensive experience in building generative AI features through prompt engineering, and fine tuning models in production environments Experience working on deep learning and generative AI frameworks li

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! The AI Research team at Figma is working on the cutting edge of AI and Design. We work on optimizing agentic systems for design quality and end user experience. We build robust evaluators for Design and post-train models. We are a very collaborative, close-knit and impact-focused team of researchers and research engineers working on some of the most challenging technical problems at the intersection of AI and creativity. We are seeking PhD interns with expertise in machine learning and artificial intelligence to develop innovative AI solutions for design and creative products. Through both fundamental and applied research, your work will contribute to new AI-driven features in Figma products. This internship can take place in Winter 2027 or Summer 2027 in San Francisco or New York. What you’ll do at Figma: Drive fundamental and applied research in Generative AI with Figma product use cases in mind Formulate and implement new modeling approaches both to improve the effectiveness of Figma’s current AI models as well as enable the launch of entirely new AI-powered product features Explore the boundaries of what is possible with the current technology set and experiment with novel ideas Depending on your project, you may have the opportunity to publish your research in leading AI/ML conferences We'd love to hear from you if you have: Are a 4th or 5th year senior Ph.D student in AI, Machine Learning, Computer Vision, Natural Language Processing, Human Computer Interaction or a related field Pro

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 . The Responsible AI team is part of the Advanced Technologies Group (ATG), Pinterest’s advanced machine learning team. ATG’s goal is to keep Pinterest at the forefront of machine learning technology across multiple use cases including recommendations, ranking, content understanding, and more. It is an applied team that works horizontally across the company on state of the art AI and ML and works on directly bringing that technology to the product in collaboration with product engineering teams. The team also publishes its work in applied research conferences, but the main goal of the team is to have a direct impact on business metrics. At Pinterest our goal is to inspire pinners (our users) to live the life they love. The product is powered by state of the art ML algorithms which are used to understand both the billions of visually rich items on

Become a part of our caring community Most AI engineering jobs are a thin wrapper around a model API. This role is different. We build the platform that transforms millions of clinical documents into trusted, actionable data. Our systems use large language models (LLMs) to read medical records, extract structured facts, answer complex questions with citations back to the source document, and route ambiguous cases to human experts for review. Our users make decisions that impact real healthcare outcomes, so “good enough” is not good enough. Building AI systems that are accurate, reliable, auditable, and scalable is at the core of this role. As a Senior AI Applied Engineer, you will design, build, deploy, and operate production AI systems used at scale within one of the largest health insurers in the United States. You will own solutions end-to-end, from user experience and APIs to model orchestration, evaluation frameworks, infrastructure, and production operations. Why Join Us Build production AI systems where LLMs are in the critical path, not just demos or proofs of concept. Work on extraction, retrieval, agentic workflows, and human-review systems that process real healthcare data at scale. Own projects end-to-end across frontend, backend, AI orchestration, infrastructure, deployment, and operations. Solve challenging problems around accuracy, explainability, traceability, and reliability in regulated environments. Ship quickly in a small, high-impact team that embraces AI-assisted development and rigorous quality standards. Build systems that continuously improve through expert feedback, evaluations, and human-in-the-loop workflows. Key Responsibilities Design, develop, and deploy full-stack AI-powered application

Become a part of our caring community You have shipped AI products before. You understand the difference between a demo and a production system. You have strong opinions about evaluation frameworks because you have experienced the consequences of operating without them. You are at your best when you own architecture decisions while continuing to build and deliver critical code yourself. We build the platform that transforms millions of clinical documents into trusted, actionable data. Our systems use large language models (LLMs) to read medical records, extract structured facts, answer complex questions with citations back to source documents, and route complex cases to human experts. The output of these systems supports healthcare decisions that impact real members. As a Lead AI Applied Engineer, you will provide technical leadership for AI-enabled products and platforms, define architectural direction, establish engineering standards, and personally design and build the most critical components of our systems. You will lead through both technical expertise and execution, helping the team deliver reliable, scalable, and auditable AI solutions in a highly regulated healthcare environment. Why Join Us Lead the architecture of production AI systems where LLMs are foundational to the product experience. Make key technical decisions regarding model selection, system boundaries, platform architecture, and build-versus-buy strategies. Own the highest-risk and highest-impact technical challenges involving reliability, explainability, and correctness. Influence engineering culture and establish standards that shape how the team builds and ships AI products. Work on systems operating at meaningful scale, processing millions of documents and supporting healthcare decisions across a large member population. Partner

Become a part of our caring community Every large organization is making critical decisions today about how it will leverage AI over the next decade. Few have leaders who can both define that vision and demonstrate its viability through hands-on engineering. This role requires both. We build the platform that transforms millions of clinical documents into trusted, actionable data. Our systems use large language models (LLMs) to read medical records, extract structured facts, answer complex questions with citations to source documents, and route difficult cases to human experts. These capabilities support decisions that impact real healthcare outcomes for members. As a Principal AI Applied Engineer, you will define the technical strategy, architectural standards, and long-term vision for AI-enabled products across the organization. You will influence enterprise-wide decisions regarding AI platforms, model strategies, engineering standards, and technology investments while remaining deeply hands-on in prototyping, experimentation, architecture, and software development. This is the highest-level individual contributor role within the AI Applied Engineering organization. Success requires exceptional technical depth, organizational influence, strategic thinking, and the ability to translate emerging AI capabilities into scalable, reliable, and responsible production systems. Why Join Us Shape the long-term AI architecture and engineering direction for a large enterprise healthcare organization. Influence how AI-enabled products are designed, built, evaluated, deployed, and governed across multiple teams. Drive strategic decisions involving models, vendors, platforms, infrastructure, and shared capabilities. Prototype and validate emerging technologies before the organization invests at scale.</

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 Post-Doctoral Researcher for our AI Research team. This 24 month fixed-term position is designed for recent PhD graduates looking to deepen their research experience on challenging problems at the frontier of AI — s pecifically, applying machine learning to high-impact real-world domains like medicine, finance, and law. You'll collaborate closely with Snowflake researchers, scientists, and engineers on fundamental and applied problems, publishing high-quality work while helping shape how AI integrates with the world's most consequential industries. AS A POST-DOCTORAL RESEARCHER AT SNOWFLAKE, YOU WILL: Collaborate with research mentors to formulate research projects or novel applications of machine learning aligned with the team's mission, with a focus on AI applied to medicine, finance, or law Conduct independent and collaborative research and publish high-quality work at top AI and domain-applied research venues Design and execute large-scale experiments using modern deep learning frameworks, writing high-quality, reusable code Develop models and systems that bridge AI capabilities with real-world application requirements in high-stakes, regulated domains Engage across teams — including with domain experts and applied engineering — to ground research in pra

About Bluevine Bluevine is the largest small business banking platform in the U.S., redefining how entrepreneurs manage their money. We create modern financial solutions, from checking and lending to payments and beyond, designed to help small business owners grow, thrive, and take control of their financial future. Our best-in-class technology, advanced security, and deep understanding of the small business community give our customers the confidence to focus on what they do best. Since 2013, we’ve supported more than 750,000 small businesses nationwide. Backed by leading investors like Lightspeed Venture Partners, Menlo Ventures, 83North, and Citi Ventures, our 500+ person global team shares one mission: to give small businesses the financial tools they need to succeed. We’re innovators driven by big ideas, collaboration, and real impact. Here, you’ll have the freedom to take ownership, grow your career, and make a difference for small business owners across America. Ready to shape what’s next? This is a hybrid role . At Bluevine, we pride ourselves on our collaborative culture, which we believe is best maintained through in-person interactions and a vibrant office environment. All of our offices have reopened in accordance with local guidelines, and are following a hybrid model. In-office days will be determined by location and discipline. Key Responsibilities: Generative AI Research: Explore and evaluate Large Language Models (LLMs) and emerging generative AI techniques to identify impactful applications in data science. Model Fine-Tuning & Adaptation: Design and execute experiments to fine-tune or customize foundational models using domain-specific and internal datasets. Applied Generative AI Solutions: Leverage generative AI to enhance traditional machine learning use cases such as risk modeling, fraud detection, and customer analytics. Prompt Engineering & Evaluation: Develop effective prompting strategies and build robust evaluation and benchma

About Decagon Decagon is the leading conversational AI platform empowering every brand to deliver concierge customer experiences. Our technology enables industry-defining enterprises like Avis Budget Group, Block’s Cash App and Square, Chime, Oura Health, and Hunter Douglas to deploy AI agents that power personalized, deeply satisfying interactions across voice, chat, email, SMS, and every other channel. We’re building a future where customer experiences are being redefined from support tickets and hold music to faster resolutions, richer conversations, and deeper relationships. We’re proud to be backed by world-class investors who share that vision, including a16z, Accel, Bain Capital Ventures, Coatue, and Index Ventures, along with many others. We’re an in-office company, driven by a shared commitment to excellence and velocity. Our values — Just Get It Done, Invent What Customers Want, Winner’s Mindset, and The Polymath Principle — shape how we work and grow as a team. About the Team Read more about the research team's work here: https://decagon.ai/blog/introducing-decagon-labs The Research team develops the model and decision-making stack that powers Decagon’s conversational agents for enterprise support. We research, adapt, and implement state-of-the-art techniques in model training, prompting, orchestration, and evaluation in order to make our agents more accurate, robust, and efficient in real-world deployments. Our goal is to push the frontier of applied conversational AI: agents that reliably understand nuanced intent, track long context, and take the right actions under uncertainty. We measure success the way customers feel it: higher resolution rates, better user satisfaction, and consistent behavior at scale. About the Role We’re looking for a manager to lead and grow a team within Decagon Research. You’ll own the team and technical roadmap for an area spanning model post-training, evaluation, safety, speech, or agent behavior, driving ambitious ideas fr

About Decagon Decagon is the leading conversational AI platform empowering every brand to deliver concierge customer experiences. Our technology enables industry-defining enterprises like Avis Budget Group, Block’s Cash App and Square, Chime, Oura Health, and Hunter Douglas to deploy AI agents that power personalized, deeply satisfying interactions across voice, chat, email, SMS, and every other channel. We’re building a future where customer experiences are being redefined from support tickets and hold music to faster resolutions, richer conversations, and deeper relationships. We’re proud to be backed by world-class investors who share that vision, including a16z, Accel, Bain Capital Ventures, Coatue, and Index Ventures, along with many others. We’re an in-office company, driven by a shared commitment to excellence and velocity. Our values — Just Get It Done, Invent What Customers Want, Winner’s Mindset, and The Polymath Principle — shape how we work and grow as a team. About the Team Read more about the Speech Research Team's work: https://decagon.ai/blog/audio-native-semantic-speaker-change-detection https://decagon.ai/blog/scaling-real-time-tts-inference https://decagon.ai/blog/teaching-flow-matching-tts-with-rl The Research team develops the model and decision-making stack that powers Decagon’s conversational agents for enterprise support. We research, adapt, and implement state-of-the-art techniques in model training, prompting, orchestration, and evaluation in order to make our agents more accurate, robust, and efficient in real-world deployments. Our goal is to push the frontier of applied conversational AI: agents that reliably understand nuanced intent, track long context, and take the right actions under uncertainty. We measure success the way customers feel it: higher resolution rates, better user satisfaction, and consistent behavior at scale. About the Role As a Research Engineer focused on Audio and Speech, you’ll be responsible for building the mode

About Decagon Decagon is the leading conversational AI platform empowering every brand to deliver concierge customer experiences. Our technology enables industry-defining enterprises like Avis Budget Group, Block’s Cash App and Square, Chime, Oura Health, and Hunter Douglas to deploy AI agents that power personalized, deeply satisfying interactions across voice, chat, email, SMS, and every other channel. We’re building a future where customer experiences are being redefined from support tickets and hold music to faster resolutions, richer conversations, and deeper relationships. We’re proud to be backed by world-class investors who share that vision, including a16z, Accel, Bain Capital Ventures, Coatue, and Index Ventures, along with many others. We’re an in-office company, driven by a shared commitment to excellence and velocity. Our values — Just Get It Done, Invent What Customers Want, Winner’s Mindset, and The Polymath Principle — shape how we work and grow as a team. About the Team Read more about the research team's work here: https://decagon.ai/blog/introducing-decagon-labs The Research team develops the model and decision-making stack that powers Decagon’s conversational agents for enterprise support. We research, adapt, and implement state-of-the-art techniques in model training, prompting, orchestration, and evaluation in order to make our agents more accurate, robust, and efficient in real-world deployments. Our goal is to push the frontier of applied conversational AI: agents that reliably understand nuanced intent, track long context, and take the right actions under uncertainty. We measure success the way customers feel it: higher resolution rates, better user satisfaction, and consistent behavior at scale. About the Role As a Research Engineer focused on Safety, you’ll be responsible for making Decagon’s AI agents safe, reliable, and controllable, from evaluation through production. You’ll identify real-world failure modes and build the models, evalua

About Decagon Decagon is the leading conversational AI platform empowering every brand to deliver concierge customer experiences. Our technology enables industry-defining enterprises like Avis Budget Group, Block’s Cash App and Square, Chime, Oura Health, and Hunter Douglas to deploy AI agents that power personalized, deeply satisfying interactions across voice, chat, email, SMS, and every other channel. We’re building a future where customer experiences are being redefined from support tickets and hold music to faster resolutions, richer conversations, and deeper relationships. We’re proud to be backed by world-class investors who share that vision, including a16z, Accel, Bain Capital Ventures, Coatue, and Index Ventures, along with many others. We’re an in-office company, driven by a shared commitment to excellence and velocity. Our values — Just Get It Done, Invent What Customers Want, Winner’s Mindset, and The Polymath Principle — shape how we work and grow as a team. About the Team Read more about the research team's work here: https://decagon.ai/blog/introducing-decagon-labs The Research team develops the model and decision-making stack that powers Decagon’s conversational agents for enterprise support. We research, adapt, and implement state-of-the-art techniques in model training, prompting, orchestration, and evaluation in order to make our agents more accurate, robust, and efficient in real-world deployments. Our goal is to push the frontier of applied conversational AI: agents that reliably understand nuanced intent, track long context, and take the right actions under uncertainty. We measure success the way customers feel it: higher resolution rates, better user satisfaction, and consistent behavior at scale. About the Role As a Research Engineer focused on Safety, you’ll be responsible for making Decagon’s AI agents safe, reliable, and controllable, from evaluation through production. You’ll identify real-world failure modes and build the models, evalua

About Decagon Decagon is the leading conversational AI platform empowering every brand to deliver concierge customer experiences. Our technology enables industry-defining enterprises like Avis Budget Group, Block’s Cash App and Square, Chime, Oura Health, and Hunter Douglas to deploy AI agents that power personalized, deeply satisfying interactions across voice, chat, email, SMS, and every other channel. We’re building a future where customer experiences are being redefined from support tickets and hold music to faster resolutions, richer conversations, and deeper relationships. We’re proud to be backed by world-class investors who share that vision, including a16z, Accel, Bain Capital Ventures, Coatue, and Index Ventures, along with many others. We’re an in-office company, driven by a shared commitment to excellence and velocity. Our values — Just Get It Done, Invent What Customers Want, Winner’s Mindset, and The Polymath Principle — shape how we work and grow as a team. About the Team Read more about the research team's work here: https://decagon.ai/blog/introducing-decagon-labs The Research team develops the model and decision-making stack that powers Decagon’s conversational agents for enterprise support. We research, adapt, and implement state-of-the-art techniques in model training, prompting, orchestration, and evaluation in order to make our agents more accurate, robust, and efficient in real-world deployments. Our goal is to push the frontier of applied conversational AI: agents that reliably understand nuanced intent, track long context, and take the right actions under uncertainty. We measure success the way customers feel it: higher resolution rates, better user satisfaction, and consistent behavior at scale. About the Role As a Research Engineer, you’ll be responsible for building industry-leading conversational AI models that power Decagon’s agent, and taking them all the way from idea to production. You’ll own multi-quarter initiatives that push the a

About Decagon Decagon is the leading conversational AI platform empowering every brand to deliver concierge customer experiences. Our technology enables industry-defining enterprises like Avis Budget Group, Block’s Cash App and Square, Chime, Oura Health, and Hunter Douglas to deploy AI agents that power personalized, deeply satisfying interactions across voice, chat, email, SMS, and every other channel. We’re building a future where customer experiences are being redefined from support tickets and hold music to faster resolutions, richer conversations, and deeper relationships. We’re proud to be backed by world-class investors who share that vision, including a16z, Accel, Bain Capital Ventures, Coatue, and Index Ventures, along with many others. We’re an in-office company, driven by a shared commitment to excellence and velocity. Our values — Just Get It Done, Invent What Customers Want, Winner’s Mindset, and The Polymath Principle — shape how we work and grow as a team. About the Team Read more about the Speech Research Team's work: https://decagon.ai/blog/audio-native-semantic-speaker-change-detection https://decagon.ai/blog/scaling-real-time-tts-inference https://decagon.ai/blog/teaching-flow-matching-tts-with-rl The Research team develops the model and decision-making stack that powers Decagon’s conversational agents for enterprise support. We research, adapt, and implement state-of-the-art techniques in model training, prompting, orchestration, and evaluation in order to make our agents more accurate, robust, and efficient in real-world deployments. Our goal is to push the frontier of applied conversational AI: agents that reliably understand nuanced intent, track long context, and take the right actions under uncertainty. We measure success the way customers feel it: higher resolution rates, better user satisfaction, and consistent behavior at scale. About the Role As a Research Engineer focused on Audio and Speech, you’ll be responsible for building the mode