Senior Software Engineer - Core AI

About this role

<p>At Qualtrics, we create software the world’s best brands use to deliver exceptional frontline experiences, build high-performing teams, and design products people love. But we are more than a platform—we are the creators and stewards of the Experience Management category serving over 18K clients globally. Building a category takes grit, determination, and a disdain for convention—but most of all it requires close-knit, high-functioning teams with an unwavering dedication to serving our customers.</p> <p>When you join one of our teams, you’ll be part of a nimble group that’s empowered to set aggressive goals and move fast to achieve them. Strategic risks are encouraged and complex problems are solved together, by passing the mic and iterating until the best solution comes to light. You won’t have to look to find growth opportunities—ready or not, they’ll find you. From retail to government to healthcare, we’re on a mission to bring humanity, connection, and empathy back to business. Join over 5,000 people across the globe who think that’s work worth doing.</p> <p style="text-align: center;"><strong>Senior Software Engineer - Socrates Experimentation Platform (SEP), Provo or Seattle</strong></p> <p><strong>Why We Have This Role</strong></p> <ul> <li>Qualtrics is seeking a Senior Software Engineer to join the Socrates Experimentation Platform (SEP) team, part of the Core AI Product Unit.</li> <li>Our mission is to enable applied scientists, data scientists, and ML engineers to rapidly build, deploy, and operate AI features and solutions at scale — by providing a unified platform and a governed data architecture.</li> <li>We build and maintain the infrastructure and workflows that power the end-to-end ML lifecycle: data ingestion and anonymization, feature engineering, model training and evaluation, and production deployment — all within AWS SageMaker Unified Studio.</li> <li>We reduce time-to-value, improve data and model quality, and lower total cost of ownership through purpose-built self-service tooling, pipeline automation, and robust operational guardrails.</li> </ul> <p><strong>How You’ll Find Success</strong></p> <ul> <li>Our team is on the cutting edge of Qualtrics’ new AI offerings.&nbsp;</li> <li>You’ll be working in a fast paced environment, and will be expected to participate in requirements gathering, design and architecture discussions, full stack development, and code reviews.&nbsp;</li> <li>You will need to take ownership of your feature and drive its development and delivery, end-to-end. Your week to week will also involve operational excellence and quality improvements.&nbsp;</li> <li>We also expect our contributors to be excellent communicators, who influence the technical direction of the team and mentor junior engineers who work alongside them.&nbsp;</li> <li>With a strong sense of ownership, and with curiosity to always try to find a better way, you will find success on this team and in Qualtrics.</li> </ul> <p><strong>How You’ll Grow</strong></p> <ul> <li>You will work on high impact projects building the platform that Qualtrics' AI teams depend on — from data ingestion and anonymization pipelines to SageMaker Unified Studio workflows.</li> <li>You will work across a breadth of AWS technologies including SageMaker Unified Studio, DataZone, Lake Formation, S3, DynamoDB, SQS, Lambda, and more.</li> <li>You will participate in design and architecture discussions with your peers, gaining insight from their experiences.</li> <li>You will work cross-functionally with applied scientists, ML engineers, data engineers, and security/compliance teams to enable success across the AI development lifecycle.</li> <li>You will communicate with various stakeholders to streamline operational effectiveness.</li> <li>You will evaluate and adopt new tools and patterns in the AWS ML and data ecosystem.</li> </ul> <p><strong>Things You’ll Do</strong></p> <ul> <li>Design and build scalable, reliable backend services and data pipelines that power the end-to-end ML lifecycle within AWS SageMaker Unified Studio.</li> <li>Own the entire lifecycle of the features and platform capabilities you work on, from ideation to delivery, collaborating closely with applied scientists, ML engineers, and product managers.</li> <li>Build and operate data infrastructure implementing a medallion (bronze/silver/gold) architecture — including ingestion, transformation, anonymization, aggregation, quality checks, and lineage.</li> <li>Operate production platform services with 99.9% availability SLOs, participating in on-call rotations and operational review processes.</li> <li>Drive self-service tooling and automation that reduces manual toil and accelerates onboarding of new AI projects.</li> <li>Teach and mentor other engineers on the team, participate in design discussions, and establish and maintain best practices through code reviews and mentorship.</li> </ul> <p><strong>What We’re Looking For On Your Resume</strong></p> <ul> <li>4+ years of relevant software engineering experience.</li> <li>Bachelor's degree in Computer Science or related field, or suitable industry experience.</li> <li>Strong proficiency in SQL for querying, analyzing, and validating large-scale data. Familiarity with other languages such as Python, Java, TypeScript, or Go is a plus.</li> <li>Deep expertise in core data engineering principles, including advanced data modeling, schema design, and processing large-scale datasets with strict data quality and validation standards.</li> <li>Proven experience leading complex, high-impact data initiatives end-to-end—from initial scoping and technical design to deployment, operational monitoring, and business-impact delivery.</li> <li>Familiarity with infrastructure-as-code (e.g. AWS CDK) and AWS cloud services; hands-on experience with SageMaker, DataZone, Lake Formation, Glue, or similar data/ML platform services is a strong plus.</li> <li>Experience building and operating data pipelines or dis