AI Native Engineer – Center for Advanced Analytics, Visualization

RTI International

. 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.

Posted 5/14/2026full-timeRemote • North Carolina • 🇺🇸 United StatesMid-LevelSenior💰 $122,000 - $150,000 per yearWebsite

Tech Stack

Tools & technologies

CloudJavaScriptMicroservicesPythonTypeScript

About the role

Key responsibilities & impact

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.
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.
contribute to new systems and enhancements that integrate with existing infrastructure, collaborating with colleagues and partners to deliver practical, production-ready solutions.
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.
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.
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.
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.
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.
contribute to testing and evaluation approaches for AI systems, including performance monitoring, reliability checks, and cost/quality trade-off analysis appropriate for federally regulated and research-driven contexts.
participate in technical discussions, workshops, and prototype development with internal teams and clients, helping gather requirements, demonstrate solutions, and iterate based on stakeholder feedback.
document systems, contribute to reusable components and shared abstractions, and support internal knowledge sharing to strengthen RTI’s AI engineering practices over time.

Requirements

What you’ll need

Master's degree and at least three years of relevant work experience building cloud-native applications such as APIs, microservices, containerization, or serverless functions; OR a Bachelor's degree with at least five years of relevant experience building cloud-native applications such as APIs, microservices, containerization, or serverless functions.
At least two years of programming experience in Python, JavaScript, TypeScript, or similar languages commonly used in AI and backend development.
Demonstrated experience contributing to the development and deployment of AI- or LLM-based systems, including retrieval pipelines, prompt design, agentic workflows, or workflow automation.
Experience working with at least one major AI platform or model provider (e.g., Anthropic Claude, OpenAI, Google Vertex AI, or open-source model serving).
Experience developing systems that work with sensitive, restricted, or confidential data, and understanding how data access, privacy, and compliance requirements influence system design.
Proficiency with shared version control (e.g., Git) and collaborative software development workflows.
Experience contributing to AI-enabled or agentic systems operating in production or research environments.
Familiarity with modern deployment and delivery practices, including CI/CD pipelines, containers, and basic infrastructure-as-code concepts.
Familiarity with basic observability practices for deployed services, such as logging, monitoring, and tracking performance or cost signals for AI-enabled systems.
Experience working in cross-functional, team-based environments, including participating in technical discussions, reviews, and iterative delivery.
Ability to contribute to AI system design and implementation within established architectures.
Strong written and verbal communication skills, with the ability to explain AI system behavior, trade-offs, and limitations to non-technical researchers, clients, and federal stakeholders.

Benefits

Comp & perks

competitive base salary
generous paid time off policy
merit based annual increases
bonus opportunities
robust recognition program
competitive range of insurance plans (including health, dental, life, and short-term and long-term disability)
access to a retirement savings program such as a 401(k) plan
paid parental leave for all parents
financial assistance with adoption expenses or infertility treatments
financial reimbursement for education and developmental opportunities
employee assistance program
numerous other offerings to support a healthy work-life balance

ATS Keywords

✓ Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

cloud-native applicationsAPIsmicroservicescontainerizationserverless functionsPythonJavaScriptTypeScriptAI systemsLLM-based systems

Soft Skills

collaborationcommunicationtechnical discussionsiterative deliveryrequirement gatheringproblem-solvingdocumentationknowledge sharingstakeholder feedbackteamwork

Certifications

Master's degreeBachelor's degree