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Company Overview
A leading healthcare organization in Massachusetts is advancing its AI and digital analytics initiatives. The company focuses on delivering innovative healthcare solutions through cutting-edge AI, agentic frameworks, and scalable technology platforms. It supports the transformation of healthcare by integrating AI engineering excellence with strategic mentorship and robust technology solutions.
About the Role
The Lead AI Engineer will guide high-performing AI engineering teams, combining deep technical expertise with strong mentorship skills. This hands-on leadership role is responsible for technical direction, delivery quality, and ensuring AI solutions are well-architected, scalable, and robust. The engineer will drive impactful AI initiatives, mentor engineers, and maintain engineering excellence while delivering innovative products.
Responsibilities
Provide technical leadership and mentorship to a team of AI Engineers, ensuring adherence to architectural best practices, coding standards, and engineering excellence
Lead the technical design and implementation of complex AI agent components, Generative AI integrations, and supporting infrastructure
Collaborate with Product Owners to refine technical requirements, estimate efforts, and ensure timely delivery of AI features
Establish and enforce rigorous code review processes to ensure code quality, security, and maintainability
Troubleshoot complex technical issues and serve as the primary escalation point for the team
Actively coach and mentor AI Engineers to grow technical skills and understanding of agentic architectures
Evaluate new tools, libraries, and frameworks to improve team efficiency and capabilities
Qualifications
Bachelor’s degree in Computer Science, Technology, or a related field
6+ years of hands-on experience in machine learning and deep learning frameworks (TensorFlow, PyTorch, scikit-learn)
3+ years of hands-on expertise in developing agentic AI solutions
Strong knowledge of cloud services (AWS, Azure, Google Cloud) and MLOps tools (Docker, Kubernetes)
Proven experience in the technical design and implementation of complex AI agent components
Hands-on experience with Retrieval Augmented Generation (RAG) architectures and fine-tuning techniques
Demonstrated ability to manage performance, scalability, and reliability of AI models in production
Excellent communication and collaboration skills with technical and non-technical stakeholders
Experience conducting code reviews, leading knowledge-sharing sessions, and making decisions on technologies and frameworks
Preferred / Standout Skills
Linux/Unix scripting experience
Experience across multiple cloud platforms (AWS, GCP, Azure)
Solution Architect Associate certifications, preferably in GCP or AWS
Disclaimer
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1. No Endorsement: Job ads on SpringCube do not imply endorsement of their authenticity or quality. 2. No Client Relationship: This company is not a client of SpringCube unless stated. 3. To Apply: Click the “Apply” button to be redirected to the hiring company’s application page for this job. 4. No Liability: SpringCube is not liable for inaccuracies.
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