What is a Software Engineer at American Institutes for Research?

At American Institutes for Research (AIR), the role of a Software Engineer goes far beyond traditional application development. You are joining a mission-driven organization dedicated to generating and using rigorous evidence to contribute to a better, more equitable world. Whether you are developing clinical quality measures, architecting data systems for healthcare innovations, or leading enterprise software transformations, your code directly supports critical social science research and public policy.

In this position, you will work at the intersection of technology, data science, and research. You will collaborate with cross-functional teams comprising statisticians, economists, and domain experts to build systems that handle sensitive data (such as CMS Medicare/Medicaid data) or streamline enterprise operations. The work requires not just technical precision but also a deep understanding of compliance, data governance, and the specific domain—be it health transformation, education, or workforce development.

This is a role for engineers who care about the "why" behind the build. You will likely face complex challenges involving large-scale datasets, interoperability standards (like FHIR and CQL), and secure computing environments. Success here means delivering robust, scalable solutions that allow AIR to fulfill its contracts with federal agencies and non-profit partners, ultimately improving lives through data-driven insights.

Common Interview Questions

Getting Ready for Your Interviews

Preparing for an interview at AIR requires a shift in mindset from "product-focused" to "mission-and-compliance-focused." You are not just being tested on your coding ability; you are being evaluated on your ability to operate within a rigorous research environment.

Domain-Specific Technical Expertise – You will be evaluated on the specific tools relevant to the track you are applying for. For healthcare roles, this means deep knowledge of health informatics (CQL, FHIR) or statistical programming (SAS, R, Python). For enterprise roles, this involves ERP platforms (PeopleSoft, Oracle). You must demonstrate hands-on mastery of these specific ecosystems, not just general programming logic.

Data Integrity and Governance – Working with federal data requires an uncompromising approach to security and accuracy. Interviewers will assess your familiarity with secure computing environments, privacy regulations (like HIPAA), and your ability to design systems that ensure reproducibility and data quality.

Consultative Communication – AIR acts as a bridge between data and policy. You will be evaluated on your ability to explain complex technical concepts to non-technical audiences, including internal project directors and external government clients. You need to show that you can translate "tech-speak" into actionable research insights.

Project Leadership and Mentorship – Many engineering roles at AIR are senior or principal level. You will be expected to discuss your experience leading cross-functional teams, mentoring junior staff, and managing competing priorities in a deadline-driven, contract-based environment.

Interview Process Overview

The interview process at American Institutes for Research is thorough and structured to ensure both technical competence and cultural alignment. Generally, the process begins with an initial screening by a recruiter to verify your background, salary expectations, and eligibility. This is followed by a hiring manager interview, which dives deeper into your specific experience with the required technology stack (e.g., health informatics tools or ERP systems) and your interest in AIR’s mission.

If you pass the initial screens, you will move to the panel stage. This typically involves a series of interviews with potential peers, technical leads, and project directors. Unlike pure tech companies that might focus heavily on whiteboard algorithms, AIR interviews often focus on practical application: discussing past projects, how you handle specific data challenges, and how you navigate regulatory constraints. You may be asked to walk through a portfolio of work, discuss a technical report you authored, or solve a domain-specific scenario (e.g., "How would you design a test plan for a new clinical quality measure?").

Throughout the process, expect a professional and respectful tone. The team is looking for colleagues who are collaborative and intellectually curious. They want to see that you can work effectively in a matrixed organization where you might support multiple projects simultaneously.

This timeline illustrates a standard progression, but keep in mind that the specific technical assessments will vary significantly based on whether you are applying for a Systems Programmer, Developer, or Director role. Use the time between the screen and the panel to brush up on the specific domain standards (like CMS data structures or ERP governance) mentioned in the job description.

Deep Dive into Evaluation Areas

Your interviews will focus on a few critical pillars. While general coding ability is important, AIR prioritizes specialized knowledge and the ability to apply it within a research context.

Domain-Specific Technical Proficiency

Because AIR hires for specific technical tracks (e.g., Health Informatics, Enterprise Systems, Statistical Programming), you will be tested on the tools of your specific trade rather than generic algorithms.

Be ready to go over:

• Health Informatics Standards: If applying for health roles, expect deep questions on FHIR, CQL, and QDM. You should know how these interact with Electronic Health Records (EHR).
• Statistical Programming: For systems programmer roles, demonstrate proficiency in SAS, Stata, R, or Python, specifically in the context of analyzing large datasets (e.g., Medicare claims).
• Enterprise Systems: For ERP roles, be ready to discuss implementation lifecycles for platforms like PeopleSoft or Oracle, including upgrades and optimizations.
• Advanced concepts: Knowledge of CMS environments (IDR, CCW, VRDC) or federal rulemaking processes regarding quality measures can set you apart.

Example questions or scenarios:

• "Describe your experience using CQL to define a clinical quality measure. What challenges did you face with data availability?"
• "How have you managed a migration or upgrade of a large-scale ERP system while minimizing downtime for finance and HR teams?"
• "Walk us through your workflow for analyzing longitudinal healthcare data in a secure environment like the VRDC."

Data Strategy and Governance

You will be working with sensitive data that drives public policy. Interviewers need to know you prioritize accuracy, security, and reproducibility above all else.

Be ready to go over:

• Data Privacy: Understanding HIPAA and secure data handling practices.
• Quality Assurance: Methodologies for validating data and testing code to ensure results are reproducible for research purposes.
• System Design: Architecting pipelines that can ingest multi-source data (claims, enrollment, survey data) efficiently.

Example questions or scenarios:

• "How do you ensure the reproducibility of your statistical programs when working with constantly updating datasets?"
• "Describe a time you identified a data quality issue in a critical report. How did you resolve it and communicate the impact to stakeholders?"

Communication and Collaboration

AIR thrives on cross-disciplinary work. You must demonstrate that you can work alongside researchers who may not be technical experts.

Be ready to go over:

• Translation: Explaining technical constraints or architectural decisions to project directors or clients.
• Proposal Writing: Contributing technical narratives to business proposals (a key part of senior roles at AIR).
• Mentorship: Examples of how you have upskilled junior team members or established coding standards.

Example questions or scenarios:

• "Tell me about a time you had to explain a technical delay or limitation to a non-technical client. How did you handle the conversation?"
• "How do you approach mentoring junior staff who are new to electronic clinical quality measures?"