• Integrate and improve existing agents into our project. • Design, develop, and configure a web application using a .NET-based backend (e.g., ASP.NET Core) and React on the frontend, leveraging the Agentic solution. • Implement Single Sign-On (SSO) integration (e.g., OAuth2/OIDC, SAML, Azure AD, or similar) to enhance user authentication and experience. • Develop and integrate RESTful APIs and external services into the .NET/React application. • Troubleshoot and resolve technical issues related to AI functionalities, agent orchestration, and system integrations. • Participate in all stages of the Software Development Life Cycle (SDLC) to deliver high-quality software solutions.

NVIDIA is looking for an AI Solutions Architect with hands-on experience in efficient AI model training and/or deployment for a customer facing role. Primary responsibilities will be to help accelerate customer workloads and lead customer technical engagements around NVIDIA software and technologies. We work with the world's most successful technology companies, and this role uniquely positions you to observe emerging industry trends at the cutting edge. Join us in this exciting endeavor! What you’ll be doing: - Collaborating closely with customers to improve their workload performance and reduce infrastructure costs. - Leading and developing proof-of-concepts for AI solutions applied to the Consumer Internet industry, including areas like LLMs and recommenders, and building collateral (notebook/code) as needed. - Developing and debugging software for NVIDIA and open-source AI frameworks and libraries. - Partnering with NVIDIA’s software engineering, product, and sales teams to secure design wins and drive the development of innovative solutions based on customer feedback. What we need to see: - BS, MS, or PhD in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, or other Engineering fields, or equivalent experience. - 8+ years of experience as an AI/Software Engineer with proven track record coding in Python and/or C++ with popular AI software libraries and GPUs. - Experience with profiling and optimizing model training/inference performance on GPUs. - Experience developing and optimizing GPU kernels for deep learning, with a focus on GEMM and attention kernels. - Strong communication skills, with the ability to clearly convey ideas and code through GitHub, documentation, and presentations. - A great teammate who enjoys collaborating with cross-functional teams including Engineering, Research, Sales, Product, and Marketing. - Self-starter with a passion for growth, continuous learning, and sharing insights with the team. Ways to stand out from the crowd: - Full stack experience from DL framework level (such as PyTorch/JAX) to lower level (such as CUDA/CUTLASS/cuDNN/NCCL). - Experience working with enterprise developers and strong customer-facing skills. - Familiarity with MLOps technologies such as containers, Kubernetes, and data center deployments. - Experience with large-scale production data pipelines and AI model training/deployment. - Creative problem-solving skills for debugging and resolving complex issues. We make extensive use of conferencing tools, but occasional travel is required for local on-site visits to customers and conferences. We are open to remote work. We look forward to having you join our team! Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family: www.nvidiabenefits.com/ Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD. You will also be eligible for equity and benefits. Applications for this job will be accepted at least until March 10, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

AI Engineer, Staff Remote - United States About the Role We're a small, funded internal startup within Blackboard building a new AI-native product. This is not a feature team, and it's not an enhancement to an existing product — we're building something categorically new, with full access to institutional infrastructure, platform data, and a direct mandate from leadership to ship in 2026. This isn't a traditional engineering team. AI coding tools — Claude Code, Cursor, and similar — generate the majority of our code. Our engineers are architects, reviewers, and product thinkers: people who know how to direct AI development agents effectively, ship features end-to-end and make judgment calls when the requirements are still evolving. On a team this small, there are no handoffs. The person who designs a feature ships it. The person who builds the data pipeline also builds the product surface that consumes it. We're looking for builders who are energized by that scope, not overwhelmed by it. Everyone on the engineering team owns features end-to-end — from the data pipeline to the AI orchestration layer to the student-facing interface. The work varies by the week, and the surface area is large. What You'll Own Product Surfaces - Student-facing product interfaces — the core user experience that learners interact with daily - Real-time features that surface AI intelligence in ways that feel immediate and useful, not mechanical - Responsive, performant UI built on a shared component library Backend & AI Integration - API routes and backend services connecting the user interface to the intelligence and data layers - AI orchestration integration: streaming responses, agent outputs, structured recommendations in context - Event-driven ingestion pipelines that translate platform activity into structured, reliable signals Data & Infrastructure - Storage architecture and schema design for persistent user state — built to evolve as the product grows - Deployment infrastructure, CI/CD, and environment management — no dedicated DevOps to hand off to - Data access controls and audit logging that satisfy institutional security and compliance requirements Quality & Velocity - End-to-end feature ownership from spec to production — including testing, monitoring, and iteration - Active use of AI-assisted development tooling to maintain high output without sacrificing code quality - Contribution to shared component libraries and codebase standards as the team grows - Stay on the bleeding edge of the AI ecosystem — Claude Code, Cursor, OpenAI Agent SDK, MCPs, and whatever comes next. When a better way to build exists, find it and bring it in. Required Skills and Experience - At least 8 years of professional experience - You work natively with AI coding tools (Cursor, Claude Code, or equivalent) — not as a curiosity, but as your actual development workflow - You've shipped products to real users — full-stack, with real accountability for whether they work - You're comfortable across the stack: React/Next.js/TypeScript on the frontend, Node.js or Python on the backend, PostgreSQL for data - You've integrated LLM APIs or built AI-powered features in production (streaming, structured outputs, agent patterns) - Strong product instincts: you notice when something feels off in the user experience and you fix it, even if it wasn't in your ticket - You can move fast, make good decisions under ambiguity, and leave the codebase better than you found it - Fluency in written and spoken English Preferred Skills and Experience - Experience with event-driven data pipelines, vector stores, or RAG pipeline design - Familiarity with infrastructure and deployment (CI/CD, managed services, observability tooling) - Background in consumer-facing products where user behavior and engagement genuinely matter About Blackboard Blackboard advances teaching excellence and unlocks the full potential of technology to deliver meaningful outcomes. We empower institutions to deepen connections between educators and learners, inspire engagement, and drive long-term academic success across the full learner journey.  For more information, please visit www.blackboard.com. The expected salary range for this position is $154,000 - $210,000. The range reflects base salary only and does not include additional compensation such as company bonus or benefits. Placement within the pay range will depend on a variety of factors, such as experience, skills, internal parity, and location. This job description is not designed to contain a comprehensive listing of activities, duties, or responsibilities that are required. Nothing in this job description restricts management's right to assign or reassign duties and responsibilities at any time.     Blackboard is an equal employment opportunity/affirmative action employer and considers qualified applicants for employment without regard to race, gender, age, color, religion, national origin, marital status, disability, sexual orientation, gender identity/expression, protected military/veteran status, or any other legally protected factor.

Fanatics Markets is the real-money prediction and trading app where you can invest in moments you care about. Built on a secure platform, we let users predict real-world outcomes and trade on events they actually follow - from sports and entertainment to political elections and beyond. Our mission is to redefine how fans engage with the moments and markets that matter most. We're looking for the right people to help us build the future of prediction markets. AI Engineer III Fanatics Betting and Gaming is seeking an AI Engineer III on our cross-functional Applied AI team that is on a mission to 10x FBG with AI. You’ll build and productionize the software foundations that power next-gen recommenders, autonomous AI agents, and scalable AI-driven experiences—working in a fast-paced, startup-style environment where you’ll move from prototype to ship-ready features in days, not months. As an AI Engineer at Fanatics, you will partner with Applied Scientists, Data Engineers, and Product teams to design, implement, and maintain end-to-end systems that deliver autonomous agent capabilities to internal stakeholders and millions of fans. You’ll translate cutting-edge research into rock-solid code, architect microservices for low-latency inference, and champion best practices in reliability, scalability, and observability. Responsibilities - Engineer Conversational ML for Support Tools Design, fine-tune, and productionize dialogue models—integrating RAG pipelines, context-aware routing, and continuous feedback loops—to power internal workflows that supercharge customer-support agents while hitting sub-100 ms latency and enterprise-grade reliability. - Develop AI Agent Frameworks Create, integrate, and extend agent orchestration pipelines—building tools to deploy, monitor, and iterate on multi-agent workflows. - Collaborate in a Startup-Like Pod Work hands-on across the stack: from data ingestion and feature engineering to model deployment and UX integration—rapidly prototyping and shipping proof-of-concepts alongside engineers and product managers. - Optimize for Scale & Reliability Implement CI/CD for model updates, containerize inference workloads (Docker/Kubernetes), and instrument services with logging, tracing, and alerts to meet 99.9% uptime SLAs. - Champion Engineering Best Practices Write clear, maintainable code; conduct code reviews; mentor junior teammates; and evangelize automated testing, code, tuning and performance monitoring. - MCP Server working on an AI platform that relates to MCP Skills & Qualifications - 7 years of professional software engineering experience, with at least 2 years focused on AI/ML systems such as conversational AI, customer support, copilot and/or chatbot experiences - Hands-on experience building and deploying models in production - Hands-on experience with MCP (Model Context Protocols) - Proficiency in Python (FastAPI, Flask) and familiarity with strong-typed languages (Java, Go, or C#) for microservice development - Experience with container orchestration (Docker, Kubernetes) and cloud platforms (AWS, GCP, or Azure) - Knowledge of AI agents and frameworks (e.g. LangChain, Ray RLlib, custom orchestrators) - Solid understanding of distributed systems, API design, and data pipelines - Comfortable navigating ambiguity in a startup-like environment: you’re resourceful, rapid in iteration, and thrive on end-to-end ownership Ready to build the future of sports betting? If you possess some of these skills but not all of them, we still encourage you to apply! Salary Range: $171,000 - $225,000 per year The base salary for this role is based on job-related knowledge, skills, and experience and may vary depending on the successful candidate’s geographic location. For information about our benefits, please visit https://benefitsatfanatics.com/ Depending on the role, your interview and onboarding experience may include in-person components, such as onsite interviews or Launching into Better: LIVE—a multi-day cultural immersion in New York City for full-time, non-seasonal hires. These sessions are designed to build connection and bring our culture to life, though specific travel and participation requirements will be confirmed based on your role and location. Your recruiter will provide clear guidance at each stage of the process. Fanatics is building a leading global digital sports platform. We ignite the passions of global sports fans and maximize the presence and reach for our hundreds of sports partners globally by offering products and services across Fanatics Commerce, Fanatics Collectibles, and Fanatics Betting & Gaming, allowing sports fans to Buy, Collect, and Bet. Through the Fanatics platform, sports fans can buy licensed fan gear, jerseys, lifestyle and streetwear products, headwear, and hardgoods; collect physical and digital trading cards, sports memorabilia, and other digital assets; and bet as the company builds its Sportsbook and iGaming platform. Fanatics has an established database of over 100 million global sports fans; a global partner network with approximately 900 sports properties, including major national and international professional sports leagues, players associations, teams, colleges, college conferences and retail partners, 2,500 athletes and celebrities, and 200 exclusive athletes; and over 2,000 retail locations, including its Lids retail stores. Our more than 22,000 employees are committed to relentlessly enhancing the fan experience and delighting sports fans globally. Launched in 2021, Fanatics Betting and Gaming is the online and retail sports betting subsidiary of Fanatics, a global digital sports platform. The Fanatics Sportsbook is available to 95% of the addressable online sports bettor market in the U.S. Fanatics Casino is currently available online in Michigan, New Jersey, Pennsylvania and West Virginia. Fanatics Betting and Gaming operates twenty-two retail sports betting locations, including the only sportsbook inside an NFL stadium at Northwest Stadium. Fanatics Betting and Gaming is headquartered in New York with offices in Denver, Leeds and Dublin.