You are:

A Software Engineer with experience building cloud-native applications and applying AI technologies to practical business, research or client needs. You have contributed to systems beyond the proof-of-concept stage and understand the engineering work required to make AI-enabled applications reliable, secure and maintainable.

You are comfortable working through ambiguity, explaining technical trade-offs and collaborating with researchers, data scientists and software engineers. You can distinguish between a compelling demonstration and a solution that is ready to support real users.

You have personally contributed to building and deploying AI-enabled applications, not just experimenting with models or using AI tools as an end user. You can clearly explain the systems you worked on, your individual contribution, the technical decisions you made, and how you evaluated whether the solution worked.

What You'll Do

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 multi-step AI 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 solutions that can be tested, deployed, maintained, and supported over time.

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.

As part of the interview process, candidates will be asked to discuss a system they personally helped build. The discussion will cover their individual contribution, key technical decisions, challenges encountered, evaluation approach and results. Candidates will also participate in a job-related technical discussion and exercise.

Responsibilities:

• AI System & Agent Development. Design, build, and maintain AI-enabled systems and multi-stepworkflows, 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 trade-off analysis appropriate for federally regulated and research-driven contexts.
• Client & Cross-Team Collaboration. Participate in technical discussions, workshops, and prototype development with internal teams and clients, helping gather requirements, demonstrate solutions, and iterate based on stakeholder feedback.
• Reusable Patterns & Knowledge Sharing. Document systems, contribute to reusable components and shared abstractions, and support internal knowledge sharing to strengthen RTI's AI engineering practices over time.

What You'll Need

Minimum Qualifications:

• 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 integrating commercial or open-source AI models into a software application through APIs or model-serving infrastructure.
• 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.
• Familiarity with modern deployment and delivery practices, including CI/CD pipelines, containers, and basic infrastructure-as-code concepts.
• Experience working in cross-functional, team-based environments, including participating in technical discussions, reviews, and iterative delivery.
• 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.
• To qualify, applicants must be legally authorized to work in the United States and should not require, now or in the future, sponsorship for employment visa status (e.g., H-1B visa status, etc.).

Preferred Qualifications:

• Experience working with AI orchestration frameworks such as LangChain, LlamaIndex, or similar tools.
• Exposure to AI orchestration or workflow frameworks, or experience building applications that coordinate multiple models, tools, or processing steps. Experience working with one or more cloud platforms such as AWS, Azure, or GCP.
• Experience working with relational and cloud-native database systems (e.g., PostgreSQL, SQL-based systems).
• Experience supporting projects in enterprise, regulated, or research-driven environments.
• Experience contributing to proposals, technical writing, or business development efforts 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.

Hiring Salary Range

$122,000 - $150,000