InterEx Group · 8 hours ago
Senior Data Scientist / AI Engineer
InterEx Group is supporting a large, rapidly expanding healthcare organization that is investing in advanced AI and Data Science capabilities. They are seeking a Senior Agentic AI Engineer to architect and implement AI solutions and integrate them across enterprise platforms while ensuring robust and scalable systems in a regulated environment.
Responsibilities
Architect and implement Agentic AI solutions, including autonomous agents, multi-agent workflows, and tool-augmented LLM systems
Build and evaluate LLM-driven pipelines, with strong rigor around tokenization, embeddings, summarization, and evaluation metrics
Translate complex business and data problems into well-structured ML and AI solutions
Apply strong classical machine learning fundamentals (sampling strategies, feature engineering, model evaluation, feature importance) to modern AI systems
Design and implement AI integrations across enterprise platforms, APIs, and data pipelines
Deploy, monitor, and optimize AI systems in cloud-based environments (AWS, Azure, or GCP)
Partner with engineering and data teams to ensure solutions are scalable, secure, and production-ready
Qualification
Required
Senior-level experience as a Data Scientist, AI Engineer, or ML Engineer in highly technical, hands-on roles
Demonstrated, practical experience with Agentic AI — beyond theoretical understanding or trend awareness
Strong depth in LLM internals, including tokenization, embeddings, summarization methods, and evaluation approaches
Solid grounding in traditional machine learning, including sampling techniques, feature importance, model validation, and performance analysis
Experience integrating AI/ML solutions into production systems
Strong cloud experience supporting enterprise-scale AI workloads
Proven critical thinking and problem-solving skills, especially in ambiguous or open-ended technical scenarios
Preferred
PhD in Computer Science, Data Science, AI, ML, or related discipline (preferred, not required)
Experience working in regulated or highly complex industries
Exposure to large-scale data platforms and enterprise AI governance practices