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. How do you make the world's most powerful coding agent for data a delight to use? We are the fastest growing software company at this scale in history and looking to push that to new heights by building the best coding agent in the industry. The Cortex Code (CoCo) team is building the future of coding agents for working with data. See our flagship product in action: CoCo Desktop in Action . As a Frontend AI Principal Engineer, you are the cornerstone of delivering the ultimate user experience. You will be entrusted with the highest level of polish, creativity, and interaction design, pushing the boundaries of what's possible in the most innovative areas of our product. This role offers the unique opportunity to have broad creative license, empowering you to lead and create groundbreaking systems and experiences that marry aesthetics with functionality, making data more accessible and actionable for our customers. AS THE FRONTEND AI PRINCIPAL ENGINEER YOU WILL: Design and build exceptional experiences, ensuring the highest level of polish, creativity, and interaction to solve complex customer problems. Define the architectural vision for the CoCo coding agent platform and ensure consistency of design abstractions across the entire product surface Develop innovative platform
Jobs in United States
Ai And Technical Learning Manager in United States
5,246 active opportunities · Updated October 2026
Showing
15 jobs
Explore current ai and technical learning manager jobs across United States. Filter by work mode, employment type, experience, department, date posted and distance.
Shape the Future with Dun & Bradstreet At Dun & Bradstreet, we believe data has the power to create a better tomorrow. As a global leader in business decisioning data and analytics, we help companies worldwide grow, manage risk, and innovate. Since 1841, businesses have trusted us to turn uncertainty into opportunity. We’re a diverse, global team that values creativity, collaboration, and bold ideas. Are you ready to make an impact and help shape what’s next? Join us! Explore opportunities at dnb.com/careers. The Senior Principal Data Scientist - AI Lead will be the point of contact for Public Sector / Government stakeholders and will be responsible for end-to-end AI solution delivery. This role will partner with U.S. government agencies on programs that depend on trusted entity data, validation, and risk insight.
Shape the Future with Dun & Bradstreet At Dun & Bradstreet, we believe data has the power to create a better tomorrow. As a global leader in business decisioning data and analytics, we help companies worldwide grow, manage risk, and innovate. For over 180 years, businesses have trusted us to turn uncertainty into opportunity. We’re a diverse, global team that values creativity, collaboration, and bold ideas. Are you ready to make an impact and help shape what’s next? Join us! Explore opportunities at dnb.com/careers. The Senior Product Manager will lead the strategy, development, and management of AI-native products within our portfolio. This role involves driving product vision, market analysis, and cross-functional collaboration to deliver innovative solutions that meet customer needs and align with business goals. The Senior Product Manager will be responsible for overseeing the product lifecycle from ideation through to launch and beyond, ensuring the product’s success in the market.
About the Team OpenAI develops models that can reason through complex problems and hardware designed for the demands of advanced AI. AI for Chips connects these efforts: applying increasingly capable AI systems to the work of semiconductor engineering. Our goal is to help engineers develop better chips and shorten design cycles. This work brings research, model training, and hardware expertise together to build tools that engineers can use on real designs, with correctness and measurable performance at the center. About the Role We’re hiring a Research Engineer to help OpenAI models solve chip-design problems through reinforcement learning, tool use, and evaluation. You’ll own experiments from the initial idea through implementation and analysis. That means building environments and evaluations, running training, investigating failures, and using the results to decide what to try next. You’ll also build the software needed to make those experiments reliable and reproducible. We value strong coding fundamentals, careful experimental judgment, and the ability to make progress independently. Prior chip-design experience is helpful, but you can learn the domain alongside the team’s hardware specialists. In this role, you will: Build RL environments and evaluations for tasks such as RTL generation, design verification, and physical design optimization. Develop and test approaches that help models use chip-design tools and improve power, performance, and area while preserving correctness. Design experiments, establish baselines, and measure whether improvements hold up on new tasks and designs. Investigate failures across model behavior, rewards, evaluation tools, and experiment infrastructure. Improve iteration speed through better tooling, faster evaluations, and proxy rewards that reflect the outcomes we care about. Turn successful experiments into reusable research code and training workflows, working closely with researchers and engineers. You might thrive in this ro
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. At Snowflake, we empower both enterprises and individuals to reach their full potential. Our culture prioritizes impact, innovation, and collaboration, making Snowflake the ideal place to build ambitious projects, execute quickly, and advance technology — and your career — to the next level. The Role We are seeking a Senior Manager, Applied Field Engineering — AI/ML Product Specialists to lead a high-performing team of AI/ML specialists at the intersection of product, field, and customer success. In this hands-on leadership role, you will manage a team of Applied Field Engineers who are deep practitioners in Snowflake's AI/ML product portfolio — including Cortex AI, ML modeling, and agentic workflows. You will drive product adoption and customer outcomes, ensuring customers move beyond initial activation to unlock the full depth of Snowflake's AI/ML capabilities. Critically, you will serve as a strategic bridge between the field and Snowflake's product organization — translating customer experience into structured product insight that directly shapes roadmap priorities. You will work closely with Product Management, Engineering, and Sales leadership to ensure Snowflake builds the right things and customers realize their full potential. Responsibilities & Focus Areas Pro
What we're building Mutiny is the self-improving AI infrastructure for GTM teams to execute faster and close more revenue. Our ambition is to do for revenue velocity what Cursor and Claude Code did for engineering velocity. With Mutiny, everyone in sales and marketing gets a bench of GTM athletes that handle any work across their revenue motion and learn from what's actually moved their deals. In April we re-launched the product as an agent-first platform. Anthropic showcased us as a leader in AI GTM. MRR is growing more than 70% month-over-month, with customers like Uber, Rippling, and Snowflake. We're backed by Sequoia, YC, and Insight, and we're building a generational company. The opportunity Most engineers spend their career making predictable systems faster. You'll spend yours making non-deterministic ones trustworthy. As a senior engineer on our AI product team, you'll architect the Campaign Builder and Agent experiences marketers and sellers open every day to go from idea to personalized assets in minutes. You'll partner directly with product, design, and the founders to define what an agent-first GTM platform should feel like, and your calls on architecture, evals, and guardrails compound across thousands of customer accounts. This role is in person in New York City, five days a week, and we ship weekly. What you'll own The core agent surfaces. Architect and ship the Campaign Builder and Agent experiences end-to-end. Frontend, backend, prompts, evals, the whole stack. Reliability on top of LLMs. Make non-deterministic models feel deterministic at the surface. Build the retries, fallbacks, and orchestration so the customer never sees the failure mode. Evals and guardrails. Define how we measure quality, catch regressions, and keep brand and tone consistent across thousands of customer accounts. Speed and feel. AI products live or die by latency and the loop between intent and output. You'll obsess over both, and use coding agents and agent networks to ship f
At ClickUp, we're building the future of work: the first truly converged AI workspace unifying tasks, docs, chat, calendar, and enterprise search, all supercharged by context-driven AI. We are an AI-native company. Every team member is expected to leverage AI daily, and we evaluate AI fluency as part of our hiring process. Join us and help redefine what's possible. 🚀 Role Overview You'll own and evolve the AI systems behind ClickUp's voice platform: real-time streaming transcription, intelligent reformatting, context-aware mention detection, and voice-to-action pipelines. This is a high-impact, hands-on role where you'll push the boundaries of what voice interfaces can do inside a productivity tool used by millions. Key Responsibilities Design, build, and optimize real-time speech-to-text pipelines (streaming ASR, VAD, audio processing) Improve transcription accuracy through context injection (user names, teams, custom vocabulary, language detection) Develop and maintain LLM-powered post-processing (grammar correction, filler removal, mention resolution, formatting) Build voice-to-action systems that parse natural language into structured workspace commands Evaluate, benchmark, and integrate ASR models (Whisper, AssemblyAI, Fireworks, etc.) for cost, latency, and accuracy Collaborate with product and platform teams to ship voice features across MAX Desktop, Mobile, Web, and Browser Extension Explore multimodal AI capabilities (screen + voice + text) for next-gen assistant experiences Equal Opportunity Employer ClickUp is an Equal Opportunity Employer, and qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, or national origin. Privacy Notice ClickUp collects and processes personal data in accordance with applicable data protection laws. You can find further details by viewing our Global Candidate Privacy Notice. If you are a Philippine Job Applicant, please also see our Phi
From $10K/yr
About Ramp Ramp is building the smart infrastructure for finance teams, embedded in the transaction flow of every dollar a business spends. We automate how over $200B in annualized spend flows in and out of 70,000+ companies: authorizing payments, flagging risk, categorizing spend, and closing books. The problems are high-stakes, data-dense, and unforgiving. We hire people with high agency and high urgency. We look for slope over intercept. We care less about where you trained and more about what you’ve built. At Ramp, everyone is a builder who owns problems end to end and makes consequential decisions that shape the outcome. The median Ramp customer saves 5% and grows revenue 16% in their first year – far in excess of businesses operating without Ramp. We believe every ambitious company deserves the same. If you want to build systems that directly shape how companies move and manage billions, Ramp is the place to do it. About the Role The Financial Intelligence team, part of Ramp's Applied AI org, powers the agentic analysis, FP&A, and book-close experiences that over 70,000 businesses rely on to run their finances. We turn messy financial data into a fast, trustworthy, governed data layer that AI agents can work with and build artifacts on top of. This is a frontend-leaning role for an engineer who obsesses over interaction design and data-dense UX, but is just as comfortable designing the API that feeds it. You'll own the surfaces customers actually touch: agentic financial analysis, month-end close, and exploratory data experiences that feel as polished as the best business intelligence tools. If you want your frontend work to sit at the center of real production LLM systems rather than being bolted on at the end, this is the role. What You’ll Do Design and ship customer-facing AI experiences end to end, from React UI through to the APIs and data contracts behind them Build BI-tool-quality interfaces for agentic analysis, FP&A, and book-close workflows:
About Ema Ema is building the world’s leading Agentic AI platform to transform enterprise productivity. We enable organizations to delegate repetitive tasks to Ema, the Universal AI Employee, delivering 10x gains in workforce efficiency, across functions. Founded by former executives from Google, Coinbase, Flipkart, and Okta, our team includes engineers from premier tech companies and graduates of Stanford, MIT, UC Berkeley, CMU, and IITs. We are backed by industry leading investors including Accel, Naspers/Prosus, Section32, and angels like Sheryl Sandberg and Dustin Moskovitz. Headquartered in Silicon Valley and with offices in London, Bangalore and Vancouver, Ema is at the frontier of what Agentic AI can do in production — we ship real systems that run real business processes at scale. At Ema, we build AI Employees that operate inside the enterprise. Healthcare is where the bar is highest: the output has to be accurate, auditable, and clinically sound. We're opening a part-time role focused on agent measurement and improvement. You'll instrument how our healthcare AI Employees perform in production, identify where quality breaks down, and design the experiments that close the gap — partnering with clinical experts to ensure improvements translate into better patient outcomes, not just better metrics. We're looking for strong analytical judgment (Python, agent lead development), comfort operating with incomplete information, and genuine interest in the healthcare domain. Clinical experience is valued but not required. This engagement is structured as a paid internship or contract engagement, with weekly syncs in our Bay Area office. Compensation offered will be determined by factors such as location, level, job-related knowledge, skills, and experience. Certain roles may be eligible for variable compensation, equity, and benefits. Ema Unlimited is an equal opportunity employer and is committed to providing equal employment opportunities to all employees and applic
About the Team The Codex Core Agent team builds the kernel of Codex. We own making the agent better, accelerating research, and making those improvements real in production for our users. That means working across the systems that make Codex actually function as an agent in the real world: the production performance envelope around tokens, latency, reliability, cost, and capacity; the core execution loop and interfaces that turn models into useful behavior; the shared infrastructure that enables other teams to build on Codex; and the feedback loops that turn real-world usage into better models and better agent behavior over time. About the Role We’re looking for applied AI engineers to help bring Codex agents from impressive demos to dependable tools. This role is about improving agent performance on real software engineering tasks and closing the gap between research capability and real-world usefulness. You’ll work closely with research, infrastructure, and product to ensure agents are not just powerful, but useful, steerable, and reliable in practice. The job is not only to improve model behavior in isolation, but to turn those improvements into measurable gains in solve rate, usefulness, and economic value for users. What You’ll Do Design and iterate on agent behaviors across real-world coding tasks and long-horizon workflows. Work closely with research to develop and run evals to measure agent performance, regressions, failure modes, and edge cases. Improve performance through prompting, tool-use strategies, context construction, and model-facing experimentation. Analyze failures in production and systematically improve robustness and reliability. Build feedback loops and data systems that get better real-task data into evaluation and research. Work with product teams to shape user-facing agent experiences and the interfaces the agent depends on. Help define what “good” looks like for agents completing complex tasks end-to-end. You Might Be a Good Fit If You Ha
About Ema Ema is building the world’s leading Agentic AI platform to transform enterprise productivity. We enable organizations to delegate repetitive tasks to Ema, the Universal AI Employee, delivering 10x gains in workforce efficiency, across functions. Founded by former executives from Google, Coinbase, Flipkart, and Okta, our team includes engineers from premier tech companies and graduates of Stanford, MIT, UC Berkeley, CMU, and IITs. We are backed by industry leading investors including Accel, Naspers/Prosus, Section32, and angels like Sheryl Sandberg and Dustin Moskovitz. Headquartered in Silicon Valley and with offices in London, Bangalore and Vancouver, Ema is at the frontier of what Agentic AI can do in production — we ship real systems that run real business processes at scale. The residency You own one hard problem end to end. You write the proposal, build the system, design the evaluation, ship behind a gate, and finish with a write-up of what turned out to be true, including the parts that didn't work. You'll sit in the production codebase with a senior mentor and real production data. Recent residents have shipped self-improving harnesses, inference-cost work, agent memory, and eval infrastructure. Your project gets scoped with you, not handed to you. The problem space The loop we care about: production traces become data, data becomes training and evaluation, and better agents produce better traces. Projects live somewhere on that loop. Harness and inference-time work. Context engineering, tool and skill design, orchestration, and deciding where extra inference compute actually pays. Self-improvement loops run behind hard fences. Post-training for agents. SFT on curated trajectories, preference optimization, RL on real agent tasks. Reward design where outcomes are verifiable, process vs. outcome supervision, distilling frontier behavior into cheaper models. Environments and rewards. Turning enterprise workflows into training and eval environments: fi
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. Snowflake is about empowering enterprises to achieve their full potential — and people too. With a culture that’s all in on impact, innovation, and collaboration, Snowflake is the sweet spot for building big, moving fast, and taking technology — and careers — to the next level. ABOUT THE ROLE: You will work on critical business initiatives in the core database engine, bring an AI-forward approach to software development and accelerate roadmap cycles for the benefit of our customers. Your work will directly impact how developers and businesses build with data. You'll own the full AI engineering lifecycle: design, prompt/tool engineering, evals, deployment, measurement, and optimization. You'll work with a small, high-powered engineering team. What you will do in this role: Own features end-to-end for Snowflake Database Engineering products. Build agentic workflows, coding harnesses, evaluation pipelines. Build enterprise-grade context engineering: function calling, tool schemas, guardrails, agent teams, and verification/repair. Design evals and hillclimb : create golden sets, create rubrics and metrics, analyze errors, run experiments to hill climb on the metrics. Partner with product and infra: translate customer problems into products and experiments. Collaborate with infr
ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to to ship AI products. THE ROLE Baseten's engineers want to work in an AI-first way. What's missing isn't enthusiasm — it's the platform underneath it. Today everyone assembles their own agent config, context files, and MCP servers, so the good patterns stay trapped in individual setups instead of becoming defaults everyone inherits. You'll build that platform: the agent configurations tuned to our monorepo, the context and tooling layer that makes agents competent in our codebase, the evals that tell us which approaches actually work, and the rollout mechanics that get a new engineer productive with agents in week one. You are not here to mandate how engineers use AI — you're here to make the good path the easy path. Success looks like teams adopting what you build because it beats what they'd cobble together themselves, not because a policy requires it. Platform engineer, not AI evangelist. Ship infrastructure, measure it, kill what doesn't work, let adoption be the referee. The playbook for AI-first SDLC doesn't exist at any company yet. You'll write ours. WHAT YOU'LL BUILD Agent substrate — Repo-level context infrastructure that makes agents competent in our codebase ( CLAUDE.md/AGENTS.md conventions, architecture and domain context, and the tooling to keep it accurate as code moves). Internal MCP servers giving agents scoped access to CI, observability, incident tooling, deployment state, and docs. Shared skills, subagents, and hooks th
ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to to ship AI products. THE ROLE: Voice is becoming the internet’s next interface, but a production-grade Voice AI system is "hard to build" . You’ll join a small founding team of Baseten Voice AI, focused on bringing state-of-the-art open source models into production for Voice AI customers across productivity, customer service, clinical conversation, creator tools, education, and more. You’ll make a meaningful impact on people’s daily lives and help reshape these industries. This is a high-impact, high-ownership role. You will be the primary owner of Baseten Voice AI - our in-house inference stack to power Voice AI models - from product roadmap through engineering implementation. You’ll partner closely with Forward Deployed Engineers, Model Performance Engineers, and sister engineering teams to push the boundaries of Voice AI. EXAMPLE INITIATIVES: Develop world-class model serving stack for state-of-the-art open-source voice models - reduce end-to-end and tail latency (p95/p99), increase throughput, and improve GPU efficiency via profiling, runtime tuning, and server-level optimizations. Build large-scale, real-time infrastructure for multi-model voice agents - orchestrate STT, TTS, and agent components with streaming I/O to meet customer SLOs. Design tight training and inference iteration loops for voice model customization - enable fast evaluation, safe rollout, and rapid experimentation for custom voice model development. Past projects:
$201K – $261K/yr
We built Bubble with a clear mission: to empower everyone to create software. Our AI visual development platform lets anyone, from first-time entrepreneurs to enterprise teams, take an idea from prompt to fully-functional, scalable app across web, iOS, and Android. With over 6 million users in more than 100 countries, Bubble is breaking down the barriers to entrepreneurship and innovation worldwide. Our Product Bubble is the only fully visual AI app builder that lets you vibe code without the code to go beyond prototypes and launch real apps to real users. Chat with AI when you want speed, edit directly when you want control. Bubble's visual editor lets you fine-tune any detail, from the design to privacy rules and programming logic, so you're never stuck, even if AI hits its limits. Everything you need comes built in: a unified web and native mobile editor, enterprise-grade hosting, security, database management, and automatic scaling that grows with your business. You can build just about anything on Bubble, and our community is living proof. Mailead grew a $10K investment into a $2M valuation, and Faceless.video went from zero to $1M+ ARR in under a year. People aren't just launching products on Bubble, they're building real businesses. See how Bubble builders are shipping apps that change industries, solve problems, and shape the future here: Inspiring builders, breakthrough apps . Why Join Bubble Now? The rise of AI-generated software has validated everything Bubble has been building toward for over a decade. But pure AI-generated code is fragile, hard to debug, and rarely production-ready. Bubble bridges that gap, combining the speed of AI with a structured visual platform that produces stable, scalable, secure software. The people who join Bubble right now will help define what that means for millions of builders around the world. If you've ever wanted to work on something that genuinely changes who gets to build, this is your moment. About the Team: We’re ex
Other cities to consider
More places hiring for this role
Get new ai and technical learning manager jobs in United States by email
Daily job updates · Unsubscribe anytime