• Design, build, evaluate, and ship LLM-based solutions that give users more adaptive control over their listening experience • Work on prompted playlist experiences with a focus on music fulfillment and session generation • Collaborate with cross-functional partners across user research, design, data science, product, and engineering • Prototype new ML approaches and bring them into production at global scale • Build and improve systems that connect artists and fans in personalized and meaningful ways • Contribute to the development of scalable ML systems serving hundreds of millions of users • Promote best practices in ML system design, testing, evaluation, and deployment across the organization • Actively contribute to a strong community of machine learning practitioners at Spotify

Role Description We are looking for an experienced Team Lead to guide our Core AI Agentic Development Team. This role demands a dual focus: maintaining a hands-on technical presence while providing mentorship, architectural guidance, and leadership to a team of Senior AI Engineers. The Team Lead will oversee the end-to-end development of complex, orchestrated agentic systems aimed at revolutionizing healthcare revenue cycle management and optimizing accounts receivable processes. - Lead the design and delivery of scalable, multi-agent AI systems, providing architectural direction for complex agent orchestration and enterprise integration. - Oversee end-to-end development of agentic applications, ensuring alignment with business goals, performance standards, and healthcare revenue cycle requirements. - Mentor and guide a team of AI engineers through hands-on technical leadership, fostering best practices in LLM development, Python engineering, and system design. - Establish and enforce engineering standards, conducting code reviews and ensuring high-quality, maintainable implementations of agent-based systems. - Architect and implement supervisor (“oracle”) agent frameworks to manage task delegation, validate outputs, and maintain system integrity. - Drive the development of agents that interact with APIs, legacy systems, and UI/voice interfaces to automate complex operational workflows. - Define and implement governance, monitoring, and guardrail strategies to ensure safe, compliant, and reliable behavior of AI systems in production. - Partner with cross-functional stakeholders (product, operations, and domain experts) to translate complex requirements into scalable technical solutions. Qualifications - Demonstrate elite technical skills expected of Senior AI Engineers, including advanced Python proficiency, production LLM deployment, and mastery of orchestration frameworks like crew.ai. - Possess deep technical knowledge in building scalable agent architectures, focusing heavily on system integration, guardrails, and governance. - Direct experience in architecting robust multi-agent orchestration systems, including the deployment of oracle/supervisor agents to manage task delegation and output verification. - Leading the development of agents that interact with legacy and modern systems via APIs, computer use (UI automation), and voice AI. - Establishing rigorous agent governance and safety guardrails to ensure compliance and reliability in production. - Experience in a team leadership or technical lead capacity, guiding software development teams through the entire product lifecycle using agile methodologies. - Conducting rigorous code reviews and establishing engineering standards specifically for agentic application development. - Mentoring engineers and fostering a culture of continuous learning around rapidly evolving AI technologies. - Collaborating with cross-functional stakeholders to translate complex requirements into actionable technical architectures. Requirements - A quiet, distraction-free environment to work from in your home. - A secure internet connection is required. - Home internet with speeds >20 Mbps for downloads and >10 Mbps for uploads. - The workspace area accommodates all workstation equipment and related materials and provides adequate surface area to be productive. Benefits - We offer paid training and incentive plans. - Our medical, dental, vision, and life insurance benefits are available from the first day of employment. - We enjoy excellent work/life balance. - Our Employee Resource Groups build community and foster a culture of belonging and inclusion. - We match 401(k) contributions. - We offer career growth opportunities. - We celebrate 12 paid holidays and generous paid time off. Company Description Revecore has been at the forefront of specialized claims management, helping healthcare providers recover meaningful revenue to enhance quality patient care in their communities. We're powered by people, driven by technology, and dedicated to our clients and employees. If you're looking for a collaborative and diverse culture with a great work/life balance, look no further.

• You'll own client launches end-to-end: validating data, selecting models, running UAT, going live, and monitoring performance afterwards. • You'll join client calls, build relationships, and understand what actually matters on the ground - not just whether the model is accurate, but whether the kitchen prepped the right amount of food.

• Design and maintain robust ML deployment pipelines to ensure seamless model delivery. • Automate model training, deployment, and monitoring workflows to increase operational efficiency. • Collaborate closely with Data Scientists and Engineering teams to integrate models into production environments. • Optimize cloud-based infrastructure to enhance the scalability and reliability of ML systems. • Implement CI/CD best practices specifically tailored for machine learning lifecycles. • Monitor production systems and proactively troubleshoot performance or governance issues.