AI Native Engineering Tech Lead

At Guild, we believe talent is everywhere and that opportunity should be too. We continue to have our home and headquarters in Denver, but we have embraced a distributed model of working to reach the best talent in the United States. While some roles may require proximity to our Denver office, roles based outside of our Denver office can sit in any of the following 32 states: AZ, CA, CO, CT, FL, GA, ID, IL, IN, KS, MA, MD, ME, MI, MN, MO, NC, NH, NJ, NV, NY, OH, OK, OR, PA, SC, TN, TX, UT, VA, WA, WI and Washington D.C. Please only apply if you are able to live and work full-time in one of the states listed above. State locations and specifics are subject to change as our hiring requirements shift. 

If you are an Internal Candidate, please apply via our Internal Job Board. 

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To thrive as a company and meet our impact goals, we must cultivate a culture of high-performance. We know managers are often the single-largest driver of employee satisfaction and growth, and our talent is our biggest asset. Because of that, we’ve identified consistent expectations for all of Guild’s people managers — helping you know what to expect from your experience here.

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Guild is hiring a Tech Lead for our AI Native Experiences team. This is a hands-on leadership role for someone excited to shape the future of AI-first product development at Guild. As a “player/coach,” you’ll set the technical vision for how we embed AI into our platform; guiding architecture, frameworks, and best practices; while also writing code and contributing to key projects.

You’ll lead a talented team of engineers in building scalable, reusable tools that make AI feel native to our products and systems. From integrating with external model APIs and internal MLOps pipelines to delivering intelligent, personalized features at scale, you’ll ensure technical excellence across the board.

Working closely with engineering management, product, design, and data science, you’ll help align roadmaps and deliver high-impact AI capabilities that serve our learners and partners. This role is central to Guild’s evolution into an AI-native product organization, where AI enhances every layer of the experience. 

Responsibilities

• Define, evolve, and implement the technical roadmap for AI-native products and systems across Guild’s web products.
• Design and develop core components and frontend infrastructure that support inference workflows - dynamic response UI, semantic search interfaces, summarization zones.
• Evaluate, select, and integrate external model APIs and internal inference pipelines in collaboration with MLOps.
• Collaborate with other cross-functional teams to ensure they are educated and equipped to use the tooling you build. Ensure standards, paved paths, and guardrails are in place to prevent fragmentation in how AI is used across teams.
• Prototype new UX interaction models (e.g. chat, autocompletion, inline generation) and bring the best into production.
• Define the technical strategy and architecture for integrating AI into Guild’s user-facing products. Choose the right tools and deployment methods to build scalable, maintainable, and secure AI-native features.
• Act as a player/coach; writing code while guiding the team through design reviews, technical challenges, and best practices in AI development. Mentor engineers to strengthen their ML and AI application skills.
• Create reusable tools, APIs, and UI components to simplify embedding AI across Guild’s products. Ensure these resources are standardized, well-documented, and easy for other teams to adopt.
• Partner with Product, Design, and MLOps to define AI feature roadmaps, assess feasibility, and align technical plans with user needs and ethical design. Ensure seamless integration of model training, deployment, and monitoring across teams.
• Monitor and optimize the performance of AI features for speed, accuracy, and reliability. Establish strong testing and alerting systems to uphold quality, security, and ethical standards in production AI systems.
• Advocate for the transformative potential of AI in education and workforce advancement.

Qualifications

• 10+ years of software engineering experience, including 3+ years in a leadership role. 
• Strong track record building scalable web applications across frontend (React/JavaScript/TypeScript) and backend (microservices, APIs, databases) systems.
• Experienced in integrating machine learning models into production systems and collaborating with ML teams on model deployment and optimization. Familiar with key concepts like model serving, inference, feature stores, and techniques such as LLMs and recommender sys