AI Ops Research Engineer-Mid -Level at USAA in San Antonio Home Office I

Job description

Why USAA? At USAA, our mission is to empower our members to achieve financial security through highly competitive products, exceptional service and trusted advice. We seek to be the #1 choice for the military community and their families. Embrace a fulfilling career at USAA, where our core values – honesty, integrity, loyalty and service – define how we treat each other and our members. Be part of what truly makes us special and impactful. We are proud to support active-duty military spouses. USAA roles may offer remote or hybrid flexibility for active-duty military spouses consistent with applicable policy and business needs. The Opportunity We are seeking a dedicated AI Operations Research Engineer-Mid -Level. The AI Operations Research Engineer conducts applied research and experimentation to identify and advance emerging AI capabilities for Application and Infrastructure Operations. The role monitors industry trends, AI/ML research, open-source technologies, and vendor capabilities, translating promising developments into prototypes and evidence-based recommendations. This hands-on role explores machine learning, generative AI, agentic AI, predictive operations, intelligent observability, and automation to determine which capabilities can improve reliability, resilience, incident management, and operational efficiency. Success is measured by turning emerging technology into validated opportunities that can inform product and engineering investment. This position will be based in San Antonio; TX and offers a flexible working environment with an on-site requirement of 5 days per week. Relocation assistance is not available for this position. What you'll do: Research emerging AI, AIOps, observability, automation, and industry trends to identify technologies and approaches with potential value for Application and Infrastructure Operations. Translate operational challenges and emerging technologies into research hypotheses, experiments, prototypes, and measurable evaluation criteria. Evaluate machine learning, generative AI, agentic AI, predictive analytics, anomaly detection, root-cause analysis, and intelligent automation for operational use cases. Develop rigorous evaluation and testing methods to assess accuracy, reliability, scalability, failure modes, production readiness, and business value. Translate validated research into technical recommendations and production opportunities, identifying which capabilities should advance, be refined, or be discontinued. Communicate research findings and recommendations to engineering, product, risk, and leadership stakeholders, including key opportunities, limitations, risks, and investment considerations. What You Have: Bachelor's degree in a STEM or Business field with applied quantitative or behavioral research fields; OR 4 years of relevant education and/or experience. 4+ years of experience in applied research, AI/ML, data science, software engineering, operations research, or related technical fields. Strong programming and analytical skills using Python and relevant AI/ML or data-analysis tools. Experience designing experiments, developing prototypes, analyzing results, and making evidence-based recommendations. Working knowledge of machine learning, statistical analysis, generative AI, and LLM concepts. Ability to rapidly evaluate emerging technologies and distinguish technical potential from production readiness. Strong written and verbal communication skills, including communicating complex findings to technical and nontechnical audiences. Knowledge of AI governance, model risk, data management, privacy, security, or operational risk principles. What Sets You Apart: Experience applying AI/ML to AIOps, observability, reliability engineering, infrastructure operations, or incident management. Experience with ML frameworks such as PyTorch, TensorFlow, or scikit-learn. Experience researching or prototyping generative AI, agentic AI, or autonomous operations capabilities. Experi