AI and Recommendation Engineer

Robert Half is partnering with an innovative healthcare technology organization that is transforming how professionals discover and consume highly specialized educational content. The team is seeking a Senior, Staff or Principal AI Search and Recommendation Engineer to lead the architecture and development of next-generation AI-powered discovery, search, recommendation, and retrieval platforms.

This role is ideal for someone who has built intelligent search and recommendation systems at scale and wants to drive both technical strategy and hands-on development.

What You'll Do

• Lead the design and development of AI-powered search, recommendation, and discovery platforms.
• Build LLM-driven user experiences that understand user intent and deliver highly relevant results.
• Develop semantic search, retrieval, ranking, and recommendation pipelines using embeddings, vector databases, and modern retrieval architectures.
• Design and implement Retrieval-Augmented Generation (RAG) solutions, knowledge retrieval systems, and AI-powered assistants.
• Evaluate emerging AI technologies, frameworks, and infrastructure to drive innovation.
• Build scalable cloud-native services supporting high-volume global users.
• Partner with Product, Data Science, and Engineering teams to prototype, test, and launch new AI capabilities.
• Define long-term AI architecture and best practices across the organization

• 10+ years of software engineering experience, including designing and building large-scale distributed applications.
• 2+ years of hands-on experience developing AI/ML-powered products, recommendation engines, search platforms, ranking systems, or personalized discovery experiences.
• Proven experience building production-scale recommendation systems, search relevance platforms, or intelligent content discovery products.
• Strong expertise in semantic search, retrieval systems, vector search, embeddings, and modern recommendation architectures.
• Production experience developing and deploying LLM-powered applications and AI-driven user experiences.
• Hands-on experience with Retrieval-Augmented Generation (RAG), knowledge retrieval, and intelligent search systems.
• Hands-on familiarity with machine learning frameworks such as TensorFlow and a practical approach to experimentation, evaluation, and model improvement.
• Strong proficiency with Python and modern backend development.
• Experience building cloud-native and distributed systems at scale.

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