Senior Software Engineer

The University of Arizona•Tucson, AZ

9d•Onsite

About The Position

The Department of Pharmacy Practice and Science trains pharmacist and scientist leaders in patient-centered care, interprofessional practice, and patient and population-oriented research. We are seeking an experienced and high-performing software developer with expertise in software engineering and agentic AI infrastructure, along with enthusiasm for working with a mid-sized academic team to develop optimized software and workflows for genomic and proteomic data analysis. The selected candidate will lead development efforts for both high-performance command-line analysis software and cloud-based web services. Visa sponsorship is not available for this position.

Requirements

Bachelor's degree in Computer Science or related field, or equivalent advanced learning attained through professional level experience required.
Minimum of 8 years of relevant work experience is required.
Ability to turn open-ended problems into concrete system architectures.
Ability to communicate effectively in both technical and non-technical contexts.
Ability to mentor and technically lead junior software engineers.

Nice To Haves

Experience setting software engineering standards across a team.
Experience designing and operating production-grade cloud services.
Mastery architecting LLM-based agentic systems, including orchestration, tool use, and evaluation.
Mastery with Linux, HPC, and cloud environments.

Responsibilities

Architect and lead development of agentic AI systems for scientific research, including multi-agent orchestration, tool-use and retrieval infrastructure, model serving and evaluation pipelines, and the abstractions that let LLM-driven agents reliably perform data wrangling, visualization, and analysis.
Responsible for translating open-ended research problems into production-quality system designs, selecting and integrating model and framework technologies, and establishing engineering standards that keep these systems robust, observable, reproducible, and maintainable at scale.
Design, write, and evaluate algorithms, software, workflows, and data management architectures supporting large-scale genomics and molecular dynamics data. Programming languages will include Python for agentic infrastructure, data management, and analysis, and Rust for speed-optimized algorithm implementations. Projects will entail development of command line tools, APIs, and cloud-based web services (both public and private cloud).
Establish and maintain industry-grade software engineering practice across the research group, including testing, continuous integration and deployment, documentation, release management, security and credential handling, and cost and resource monitoring.
Provide implementation and administration of workflow systems, containerization frameworks, and deployment onto national computational infrastructure such as DOE and NSF-supported HPC and cloud resources.
Provide technical leadership, mentoring, and training for software engineers, graduate students, and undergraduate researchers, including code review, architectural guidance, and establishing shared engineering conventions.
Contribute to grant development, strategic planning of the group's technical direction, and representation of the group's software and AI infrastructure work to collaborators, funding agencies, and the broader scientific community.