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AI Engineering Manager - Internal AI Agent Jobs

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Senior Manager, Software Engineering - Agentic AI Solutions
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Lead the development of transformative Agentic AI solutions in healthcare. This senior engineering role requires deep expertise in distributed systems, AI integration, and leading high-performing teams. You will build intelligent co-pilots and automations within critical platforms like Epic. Enjo...
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United States , New York
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215000.00 - 275000.00 USD / Year
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K Health
Expiration Date
Until further notice
Lead the forefront of intelligent automation as an AI Engineering Manager for internal AI agents. This pivotal leadership role sits at the intersection of artificial intelligence, software engineering, and strategic business process improvement. Professionals in these jobs are responsible for building and managing a team of machine learning engineers, software developers, and data specialists to design, develop, and deploy AI agent systems that operate within a company's internal ecosystem. These autonomous or semi-autonomous agents are tasked with streamlining operations, enhancing productivity, and solving complex internal challenges, from IT support and HR onboarding to data analysis and workflow automation. A typical day involves translating high-level business needs into a tangible AI roadmap. Common responsibilities include overseeing the entire agent lifecycle—from conceptualization and data pipeline architecture to model training, integration, deployment, and continuous monitoring. AI Engineering Managers prioritize projects, allocate resources, and ensure robust, scalable, and ethical AI solutions. They establish best practices for development, implement rigorous testing frameworks for agent reliability, and foster a culture of innovation and collaboration. Crucially, they act as the bridge between executive stakeholders, cross-functional teams, and technical staff, ensuring alignment with organizational goals. To excel in these jobs, candidates typically require a strong blend of technical and leadership skills. A deep understanding of machine learning (especially NLP, reinforcement learning, and LLMs), software architecture (cloud services, APIs, microservices), and data engineering is fundamental. Equally important are proven team management abilities, project management expertise, and exceptional communication skills. Most positions demand a graduate degree in Computer Science, AI, or a related field, coupled with hands-on experience in building ML systems and a track record of leading technical teams. Successful managers in this domain are strategic thinkers, adept at navigating ambiguity, and passionate about leveraging AI to create tangible internal value, making these roles critical for organizations investing in their intelligent infrastructure. Explore AI Engineering Manager jobs to lead the teams building the intelligent backbone of modern enterprises.

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