AI Native Engineer - Center Advanced Analytics & Visualization

Why RTI

RTI International is an independent, scientific research institute dedicated to improving the human condition. Our vision is to address the world's most critical problems with technical and science-based solutions in pursuit of a better future. Clients rely on us to answer questions that demand an objective and multidisciplinary approach—one that integrates expertise across social, statistical, data, and laboratory sciences, engineering, and other technical disciplines to solve the world's most challenging problems.

We believe in the promise of science and technical solutions, and we push ourselves every day to deliver on that promise for the good of people, communities, and businesses in the US and around the world. If you are looking for the opportunity to make a real difference, RTI is the place for you.

You are:

An AI Native Engineer with experience building cloud-native applications and deploying AI-driven solutions in production environments. You are a pragmatic problem solver who operates effectively in ambiguity while delivering well-scoped, production-ready systems, with exposure to agentic workflows and growing enterprise AI expertise.

You design, build, and iterate on AI-enabled systems that improve workflows and deliver measurable value. You understand that AI systems in a research organization must meet a high bar of rigor comparable to survey methodology, clinical trials, and systematic reviews.

At this level, you contribute to AI architecture and technical decisions, support proposal development, collaborate closely with senior engineers and leadership, and help mentor junior team members while advancing RTI's AI capabilities.

The Work:

You will work closely with internal teams and clients to contribute to the design, development, and deployment of AI-powered solutions across sectors such as health, energy, and education. You will help translate business and research needs into technical implementations, build and refine agentic workflows, and support the delivery of scalable, secure systems in enterprise environments.

You will contribute to new systems and enhancements that integrate with existing infrastructure, collaborating with colleagues and partners to deliver practical, production-ready solutions.

In this role, you will support the development of AI systems and enhancements that integrate with RTI's research infrastructure—including survey data collection platforms, systematic review pipelines, data quality assurance systems, and proposal development workflows—working closely with data scientists, domain researchers, and software developers to ensure solutions meet the rigor expected in federally regulated and research-driven environments.

This position offers flexibility to be based at our headquarters in Research Triangle Park, NC, or to work remotely.

• AI System & Agent Development. Design, build, and maintain AI-enabled systems and agentic workflows, including retrieval, tool use, orchestration, and iterative improvement, with a focus on production readiness and maintainability.
• Enterprise & Research Infrastructure Integration. Contribute to AI systems that integrate with and extend RTI's existing platforms—such as survey data collection, systematic review pipelines, data quality assurance tools, and proposal workflows—working within established architectures and constraints.
• Cloud Native Engineering. Develop and deploy cloud-native services using APIs, containers, and modern CI/CD practices, contributing to scalable, secure, and cost‑aware AI solutions in enterprise environments.
• Workflow Translation & Automation. Translate research, business, and client needs into working AI applications that automate or augment workflows, collaborating closely with data scientists, researchers, and software engineers to ensure practical value and methodological rigor.
• Evaluation, Quality, and Reliability. Contribute to testing and evaluation approaches for AI systems, including performance monitoring, reliability checks, and cost/quality tradeoff analysis appropriate for federally regulated and research‑driven contexts.
• Client & Cross…