About this role.
Dscout is seeking a senior AI Data Engineer to build and own reliable data pipelines, warehouse models, and infrastructure supporting production AI features. The role partners closely with machine-learning and analytics engineering teams to deliver trustworthy data, reporting, evaluation harnesses, and ongoing production monitoring. Candidates need at least five years of data-engineering experience, strong Python skills, and hands-on experience operating ML or AI systems used by real customers. The environment emphasizes high agency, clear written communication, quality ownership, and the ability to drive ambiguous work to practical outcomes. The position is remote within the United States, excluding Montana, Hawaii, Alaska, and Washington, DC.
Role DNA
A quick view of the complexity, pace, ownership and collaboration implied by the job description.
Job Complexity
5/5Pace & Pressure
4/5Autonomy Level
5/5Communication Load
4/5Salary analysis
Estimated compensation compared with the broader US market for similar roles.
Core skills
Skills and capabilities most closely associated with this opportunity.
Cover letter sample
Dear Hiring Team,
I am excited to apply for the AI Data Engineer role at Dscout. My experience building reliable Python-based data pipelines, warehouse models, and production ML infrastructure aligns well with Dscout’s need for trustworthy AI features and research reporting.
I would bring a quality-first approach to orchestration, monitoring, evaluation harnesses, and cross-functional collaboration with ML and analytics engineering partners. I am particularly motivated by the opportunity to turn rich behavioral data into dependable systems that improve how researchers understand people.
Thank you for your consideration; I would welcome the opportunity to discuss how I can contribute to Dscout’s data and AI platform.
Sample interview questions
I would describe a pipeline I owned end to end, including source contracts, incremental loading strategy, orchestration, warehouse modeling, observability, and data-quality checks. I would quantify its scale and reliability outcomes and explain how I handled schema changes, backfills, and failures.
I would begin by defining the feature’s user outcome and concrete failure modes, then build representative test datasets with expected outputs and measurable quality thresholds. I would pair offline evaluations with production monitoring for drift, latency, cost, and user-impact signals, using release gates and periodic review to keep quality durable.
I would explain how I establish shared definitions, document source-of-truth models, and use version-controlled transformations and tests. I would involve analytics partners early to validate metric logic and ensure dashboards remain understandable and trustworthy as product data evolves.
I would use Airflow or Dagster to make dependencies, retries, alerts, lineage, and backfills explicit. I would keep tasks idempotent, isolate credentials and configuration, add freshness and volume checks, and provide actionable runbooks so failures can be diagnosed quickly.
I would first clarify the business decision, affected users, acceptable risks, and the smallest viable outcome. I would then propose a staged plan, communicate assumptions and tradeoffs early, deliver an observable initial version, and use results to refine the system without waiting for a fully specified ticket.
At Dscout, we’re building the most flexible and powerful UX research platform on the market—trusted by the world’s top brands in finance (JP Morgan Chase, Intuit, Charles Schwab, PayPal), healthcare (Aya, Headspace), consumer goods (Keen, Verizon, Target, Northface), and tech (Google, Amazon, Facebook, Meta, Spotify, AirBnB). Our tools help teams deeply understand the humans behind their products, so they can build better ones. We are expanding our smart and driven team and would love for you to join us.
AI is a core part of how Dscout operates. Feature quality relies heavily on the data pipelines and infrastructure under the hood. As an AI Data Engineer you will be at the intersection of ML systems and data engineering, working closely with our MLE and analytics engineering teams to build the pipelines, models, and evaluation systems that make our AI features trustworthy in production.
Dscout sits at a unique intersection: a platform where rich human behavior data meets the researchers trying to make sense of it. Getting that data right: structured, trustworthy, and ready to power both AI features and the reporting researchers rely on is foundational work. That’s what this role is about.
What you’ll do
- Design, build, and own the data pipelines that move and transform data from our application and third-party sources into relational databases – keeping them reliable and well-modeled as volume and complexity grow
- Partner with analytics engineering to build the data models and reporting that give researchers and teams real visibility into how their work is performing
- Own data quality as a first-class concern across ingestion, modeling, and reporting. Catch problems before they reach a model, a dashboard, or a user, and fix them
- Build and ship production AI systems the data infrastructure and services that ML features run on
- Design and own evaluation systems that tell us whether an AI feature is ready to ship and holding up over time: eval harnesses, test datasets, and production monitoring built as software, not one-off analyses
- Set the standard for how data work gets done. Write clearly, share context early, and make the people around you faster
What you bring
- 5+ years of experience in data engineering, with meaningful exposure to ML systems in production
- Deep data engineering experience: you’ve personally built and owned pipelines that move data from application sources into a warehouse at scale, and you know what breaks, when, and why
- Strong Python skills and fluency across the data stack (we use Snowflake and Postgres)
- Experience with orchestration tools like Airflow, Dagster, or similar
- Experience working with cloud computing environments like GCP or AWS.
- A track record of working closely with analytics engineers or data analysts to build reliable, well-documented data models
- Hands-on experience shipping AI or ML systems that real users depended on in production, and owning what happened after launch
- A genuine point of view on evaluation: you treat evals as something you build, not a report you write
- A high-agency mindset. You can take an ambiguous problem and drive it to a working outcome without a fully-scoped ticket
- Fluency across the data lifecycle, from production-facing features to the internal analytics that drive decision-making
- Comfort working across the data lifecycle, from production-facing features to the internal analytics that drive decision-making
- Comfort using AI coding tools (Cursor, Claude Code, Copilot, or similar) as a real part of your workflow
Nice to have
- Experience with dbt or similar data modeling frameworks
- Familiarity with LLM evaluation and observability tooling
- Exposure to MCP-based tooling or agentic data workflows
If this role excites you but you’re not sure you check every box, we’d still love to hear from you.
Of course, what is outlined above is an ideal set of expectations; however, business needs and other projects and tasks may shift, and additional tasks could be assigned at the discretion of your manager.
About Dscout
Dscout is a team of passionate, empathetic, and curious professionals. As a recognized leader in the Forrester Wave, we’re at the cutting edge of experience research technology. The power of research drives us – how in-context insights from real people can build more enjoyable products and services.
We prioritize learning, sharing, and building. We also deeply value being a diverse and inclusive team and company and look for team members who align with that belief. Join our dynamic team and help shape product roadmaps and business strategies for the world’s most loved brands.
It doesn’t stop there. When you join the Dscout team, you will get:
- A strong and competitive compensation package with a built-in bonus and equity program.
- An incredible and progressive benefits package (for both you and your dependents) to support work/life balance, including flexible PTO, 15 company holidays, 12 weeks of paid parental leave, 401k match, and much more.
- An education stipend to support your growth & development, and a remote work stipend.
- A company that is open and transparent with our team. You will know what is happening and why it matters.
Dscout is an equal-opportunity employer that values diversity. We do not discriminate based on identity, including race, color, religion, national origin or ancestry, sex, gender identity and expression, age, physical or mental disability, pregnancy, veteran or military status, unfavorable discharge from military service, genetic information, sexual orientation, marital status, order of protection status, citizenship status, arrest record or expunged or sealed convictions, or any other legally recognized protected basis under federal, state, or local law.
If you need reasonable accommodations for any part of the employment process, please email us at accommodations@dscout.com with the nature of your request and your contact information. We’ll do everything possible to ensure you’re well-prepared for success during our interview process, while also upholding your privacy, including accommodating any special requests. Please note that only inquiries regarding requests for reasonable accommodation will be responded to from this email address.
When you apply at Dscout, we will process your job applicant data, including your employment and education history, transcript, writing samples, and references, as necessary to consider your job application for open positions. For more information about our privacy practices, please visit our Privacy Policy.
Dscout participates in the E-Verify program in certain locations, as required by law.
Location Flexibility: Dscout is proud to support a remote-first workforce and enable employees to work from almost anywhere. At this time, however, we are unable to hire in the following locations: Montana, Hawaii, Alaska, and Washington DC.
NOTE: DSCOUT NEVER CONTACTS JOB APPLICANTS VIA TEXT, MESSENGER, OR OTHER SIMILAR APPLICATIONS. BE AWARE OF PHISHING AND SPOOFING SCAMS, BOTH VIA TEXT AND EMAIL. ONLY RESPOND TO EMAILS FROM DSCOUT.COM
Annual salary information is not provided for this position. Explore salary ranges for similar roles in our Salary Directory ›
Upload your resume now
- To unlock remote work opportunities and be discovered by global employers.
This job listing has been manually reviewed by the Jobicy Trust & Safety Team for compliance with our posting guidelines, including verification of the company's legitimacy, accuracy of job details, clarity of remote work policy, and absence of misleading or fraudulent content.
