We are looking for an Artificial Intelligence (AI) Engineer to help turn promising AI concepts into reliable, scalable solutions used across the business. This role works closely with technology, product, and operational teams in Conshohocken, Pennsylvania to guide practical delivery decisions, strengthen production AI systems, and ensure solutions are secure, governable, and useful for everyday workflows. The ideal candidate combines hands-on engineering depth with strong judgment, enabling teams and stakeholders to move from experimentation to measurable business impact.<br><br>Responsibilities:<br>• Collaborate with cross-functional technology and product teams to advance AI initiatives from early testing into stable production environments while aligning with existing ownership across the organization.<br>• Design, build, and support production-ready AI systems, while providing technical guidance and mentorship to other engineers contributing to delivery efforts.<br>• Define and improve the end-to-end productionization process for AI solutions, including system architecture, model evaluation, performance optimization, cost management, observability, and continuous iteration.<br>• Embed AI capabilities into operational workflows so that teams gain practical adoption, improved efficiency, and stronger output quality rather than isolated proof-of-concept results.<br>• Apply responsible AI practices that support healthcare-oriented expectations around privacy, security, governance, and model oversight without slowing delivery unnecessarily.<br>• Assess third-party platforms, vendors, and integration approaches to identify scalable options and avoid tools that create fragmented or short-term solutions.<br>• Drive automation opportunities across content and compliance-related processes to create more efficient and differentiated delivery capabilities.<br>• Contribute technical expertise during client discussions, proposals, and new business efforts by clearly representing what can be built and delivered in real-world timelines.<br>• Engage confidently with client and internal stakeholders across IT, brand, medical, and agency functions, translating technical considerations into practical business decisions.<br>• Help non-technical users adopt AI tools by promoting governed, accessible solutions that fit the needs of teams beyond engineering.

• Experience building and deploying machine learning or AI solutions in production environments rather than limiting work to prototype development.<br>• Strong knowledge of artificial intelligence and machine learning concepts, with the ability to evaluate feasibility, scalability, and operational impact.<br>• Hands-on experience with TensorFlow and related frameworks used for model development, deployment, and lifecycle management.<br>• Background in computer vision and detection use cases, including designing or supporting models for real-world applications.<br>• Ability to work across technical and non-technical teams and communicate clearly with stakeholders in client-facing and internal settings.<br>• Understanding of architecture, monitoring, latency, cost considerations, and evaluation methods for production AI systems.<br>• Familiarity with privacy, security, and governance practices relevant to regulated environments such as healthcare or life sciences.<br>• Capability to assess vendors, platforms, and integration patterns with a focus on usability, scalability, and long-term value.

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