Design and build scalable backend services and data pipelines to power the end-to-end ML lifecycle in AWS SageMaker Unified Studio. Own features from ideation to production, implement a medallion data architecture, ensure 99.9% SLO reliability with on-call responsibilities, drive self-service tooling and automation, and mentor engineers while collaborating with applied scientists, ML engineers, and security teams.
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.
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.
Senior Software Engineer - Socrates Experimentation Platform (SEP)
Why We Have This Role
- Qualtrics is seeking a Senior Software Engineer to join the Socrates Experimentation Platform (SEP) team, part of the Core AI Product Unit.
- 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.
- 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.
- 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.
How You’ll Find Success
- Our team is on the cutting edge of Qualtrics’ new AI offerings.
- 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.
- 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.
- 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.
- 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.
How You’ll Grow
- 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.
- You will work across a breadth of AWS technologies including SageMaker Unified Studio, DataZone, Lake Formation, S3, DynamoDB, SQS, Lambda, and more.
- You will participate in design and architecture discussions with your peers, gaining insight from their experiences.
- You will work cross-functionally with applied scientists, ML engineers, data engineers, and security/compliance teams to enable success across the AI development lifecycle.
- You will communicate with various stakeholders to streamline operational effectiveness.
- You will evaluate and adopt new tools and patterns in the AWS ML and data ecosystem.
Things You’ll Do
- Design and build scalable, reliable backend services and data pipelines that power the end-to-end ML lifecycle within AWS SageMaker Unified Studio.
- 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.
- Build and operate data infrastructure implementing a medallion (bronze/silver/gold) architecture — including ingestion, transformation, anonymization, aggregation, quality checks, and lineage.
- Operate production platform services with 99.9% availability SLOs, participating in on-call rotations and operational review processes.
- Drive self-service tooling and automation that reduces manual toil and accelerates onboarding of new AI projects.
- Teach and mentor other engineers on the team, participate in design discussions, and establish and maintain best practices through code reviews and mentorship.
What We’re Looking For On Your Resume
- 4+ years of relevant software engineering experience.
- Strong backend development experience in Python; familiarity with other languages such as Java, TypeScript, or Go is a plus.
- Experience building and operating data pipelines or distributed data systems (e.g. ETL/ELT, event-driven architectures, SQS/Kafka, S3-based data lakes).
- Familiarity with AWS cloud services; hands-on experience with SageMaker, DataZone, Lake Formation, Glue, or similar data/ML platform services is a strong plus.
- Familiarity with infrastructure-as-code (e.g. AWS CDK).
- Familiarity with different database technologies across SQL and NoSQL options.
- Experience with professional software engineering practices such as unit testing, code reviews, and writing design documents.
- Experience owning deployment and operations for large-scale distributed systems.
- Bachelor's degree in Computer Science or related field, or suitable industry experience.
What You Should Know About This Team
- The Socrates Experimentation Platform (SEP) team is the foundational AI infrastructure team within Qualtrics' Core AI Product Unit. We own the data mesh, ML platform, and self-service tooling that applied scientists and ML engineers across Qualtrics depend on.
- Our platform is built around AWS SageMaker Unified Studio and implements a governed medallion data architecture, ensuring high-quality, legally-compliant, and discoverable datasets for AI development.
- We operate with a product mindset — our roadmap is driven by user outcomes like time-to-first-production and researcher satisfaction, validated through close design partnerships with our customers.
- We care deeply about reliability, security, and cost efficiency — we run 24/7 on-call for critical services, enforce policy-as-code for data privacy, and build cost guardrails into everything we ship.
- We are looking for an engineer who is passionate about enabling other builders — someone who works well across disciplines, takes pride in platform quality, and can empathize with the needs of researchers and scientists who depend on our tools.
Our Team’s Favorite Perks and Benefits
- Qualtrics Annual Experience Bonus ($1,800) can be used for an experience of your choosing: concerts, vacation, event tickets, etc.
- Global Wellness Benefit ($1,200) reimburses employees to stay on top of their health and wellness.
- Quarterly team offsite team building events.
- Great standard benefits package (medical, dental, vision, life insurance, 401k, etc).
- Snacks, drinks, and free lunches in our office.
The Qualtrics Hybrid Work Model: Our hybrid work model is elegantly simple: we all gather in the office three days a week; Mondays and Thursdays, plus one day selected by your organizational leader. These purposeful in-person days in thoughtfully designed offices help us do our best work and harness the power of collaboration and innovation. For the rest of the week, work where you want, owning the integration of work and life. #hybrid
Qualtrics is an equal opportunity employer meaning that all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other protected characteristic.
Applicants in the United States of America have rights under Federal Employment Laws:Family & Medical Leave Act,Equal Opportunity Employment,Employee Polygraph Protection Act
Applicants in the United States of America have rights under Federal Employment Laws:Family & Medical Leave Act,Equal Opportunity Employment,Employee Polygraph Protection Act
Qualtrics is committed to the inclusion of all qualified individuals. As part of this commitment, Qualtrics will ensure that persons with disabilities are provided with reasonable accommodations. If reasonable accommodation is needed to participate in the job application or interview process, to perform essential job functions, and/or to receive other benefits and privileges of employment, please let your Qualtrics contact/recruiter know.
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For full-time positions, this pay range is for base per year; however, base pay offered within this range may vary depending on location, job-related knowledge, education, skills, and experience. A sign-on bonus and restricted stock units may be included in an employment offer. Full-time employees are eligible for medical, dental, vision, life and disability, 401(k) with match, paid time off, a wellness reimbursement, mental health benefits, and an experience bonus. For a detailed look at our benefits, visit Qualtrics US Benefits.
Washington State Base Annual Pay Transparency Range
$168,000—$221,000 USD
Qualtrics Seattle, Washington, USA Office
1201 2nd Ave, Floor 17, Seattle, WA, United States, 98101
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