Software Engineer - AI Applications

What you’ll work on

You will partner with internal teams and clients to translate research and business needs into working AI systems. Responsibilities include contributing to new solutions and enhancements that integrate with existing infrastructure, with an emphasis on delivery that can be tested, deployed, maintained, and supported over time.

• Design, build, and maintain AI-enabled systems and multi-step workflows that support retrieval, tool use, orchestration, and iterative improvement.
• Integrate AI systems with RTI platforms, including survey data collection, systematic review pipelines, data quality assurance systems, and proposal development workflows.
• Develop and deploy cloud-native services using APIs, containers, and modern CI/CD practices to support scalable, secure, and cost-aware AI solutions.
• Contribute to testing and evaluation approaches, including performance monitoring, reliability checks, and cost/quality trade-off analysis for federally regulated and research-driven contexts.
• Support documentation, reusable components, and shared abstractions to strengthen RTI’s AI engineering practices over time.

Collaboration and stakeholder impact

In this role, you will participate in technical discussions, workshops, and prototype development with internal teams and clients. You will help gather requirements, demonstrate solutions, and iterate based on stakeholder feedback, including explaining AI system behavior and limitations to non-technical audiences.

Requirements

• Master’s degree and at least 3 years of relevant experience building cloud-native applications such as APIs, microservices, containerization, or serverless functions; OR Bachelor’s degree with at least 5 years of relevant experience in similar work.
• At least 2 years of programming experience in Python, JavaScript, TypeScript, or similar languages used in AI and backend development.
• Experience contributing to the development and deployment of AI- or LLM-based systems, including retrieval pipelines, prompt design, agentic workflows, or workflow automation.
• Experience integrating commercial or open-source AI models via APIs or model-serving infrastructure.
• Experience working with sensitive, restricted, or confidential data, including how privacy and compliance requirements influence system design.
• Proficiency with shared version control (e.g., Git) and collaborative development workflows.
• Familiarity with modern deployment and delivery practices such as CI/CD, containers, and basic infrastructure-as-code concepts.
• Ability to work effectively in cross-functional teams and contribute in reviews, discussions, and iterative delivery.
• Strong written and verbal communication skills to explain AI behavior, trade-offs, and limitations to researchers, clients, and federal stakeholders.
• Applicants must be legally authorized to work in the United States and should not require sponsorship for employment visa status (e.g., H-1B), now or in the future.

Preferred qualifications

• Experience with AI orchestration frameworks such as LangChain, LlamaIndex, or similar tools.
• Exposure to orchestration or workflow frameworks, or experience coordinating multiple models, tools, or processing steps, with one or more cloud platforms such as AWS, Azure, or GCP.
• Experience with relational and cloud-native database systems (e.g., PostgreSQL and SQL-based systems).
• Experience supporting projects in enterprise, regulated, or research-driven environments.
• Experience contributing to proposals, technical writing, or business development in a research or federal contracting context.
• Proficiency with Unix/Linux command-line environments.
• Interest in growing into more senior AI engineering or technical leadership roles within a collaborative, research-driven environment.

Technologies you may use

• Python, JavaScript, TypeScript, Git, APIs
• Microservices, containerization, serverless functions
• Retrieval pipelines, prompt design, agentic workflows, workflow automation
• CI/CD pipelines, containers, infrastructure-as-code
• LangChain, LlamaIndex, AWS, Azure, GCP
• PostgreSQL, Unix/Linux

Benefits

• 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

Interview process

• Candidates will be asked to discuss a system they personally helped build, including individual contribution, key technical decisions, challenges encountered, evaluation approach, and results.
• Candidates will also participate in a job-related technical discussion and exercise.

Location preference

RTI strongly prefers candidates located within reasonable driving distance of RTI’s headquarters in Research Triangle Park, North Carolina, to support periodic in-person collaboration, team meetings, and other on-site activities as needed.