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Remote

Staff Software Engineer, Data

stabilityaiRemotePosted 27 Oct 2026

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About this role

The Team The Data team builds and runs the systems that make Stability AI's data usable, both to operate the business and to train our models. We're a small, collaborative team that works closely with Finance, Marketing, SRE, Security, Product and Research. We focus on outcomes rather than hours, and you'll have deep technical access and the freedom to build. Our stack: AWS (S3, Athena, Glue, EMR, Step Functions, EventBridge), Iceberg, dbt, Postgres, Terraform, Helm, GitHub Actions, QuickSight, Stripe, Auth0, HubSpot, Customer.io, PostHog, OpenTelemetry and SLURM — or similar.

We care about the judgement more than the logo. The Work You'll own our company data platform end to end: the AWS data lake, the transformation layer, the integrations between our business systems, and the Kubernetes-based infrastructure they run on. The data that runs the business (billing, usage telemetry, identity, CRM, ERP, cloud cost) lives in a dozen systems that were never wired together. You'll be the engineer who connects them and keeps them reliable.

You'll also be the data engineer for our research teams across audio, video, image and 3D, building the pipelines that turn raw media into training-ready datasets. This is a hands-on role with real ownership, not a data-prep or analyst seat. Own the company data platform end to end: the S3/Athena/Glue lake, the dbt project and its daily build, ingestion from Stripe, Auth0, HubSpot, OpenTelemetry and product events, and the Postgres serving layer for dashboards and AI agents Build and operate integrations between billing, CRM, ERP, identity and telemetry systems so revenue, usage, cost and customer identity reconcile automatically instead of through spreadsheets and tickets Design and maintain the warehouse layer: dimensional models, data contracts with product engineering for event schemas, quality tests, lineage and a catalog Enforce PII tiering (open vs.

restricted schemas) through access grants, working with Security and Legal Process data at scale: billions of telemetry rows, terabyte log streams, Iceberg tables, partitioning and cost control Own orchestration and infrastructure: orchestration on EKS, Helm, Terraform, CI/CD, monitoring and alerting, and join the business-hours on-call rotation for the daily pipelines Deliver operational reporting for Finance and leadership: revenue by business line, credits and prepaid liability, and cloud cost by department Support the research teams across every modality: source, license-check, ingest and version large training datasets for audio, video, image and 3D Build the generation, filtering, deduplication and captioning pipelines that turn raw or synthetic media into training-ready shards, and run them at scale on our SLURM cluster and cloud object storage Keep lineage, quality metrics and dataset documentation current so any researcher can reproduce a training set Lead design reviews, mentor teammates and write the runbooks that remove single-person dependencies Partner with Finance, Marketing, SRE, Security, Product and Research on company-wide data initiatives What You Bring We're looking for an engineer who pairs strong software engineering habits with warehouse.

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The ideal candidate combines strong software engineering habits with warehouse modelling depth, and the judgement to say what a number means and what it does not. Experience 6+ years building and running production data platforms, including ownership of the architecture Experience integrating SaaS business systems (Stripe, HubSpot, an ERP, an identity provider) into a warehouse Production experience preparing large multimodal training datasets and running batch workloads on HPC or cloud schedulers (SLURM, Kubernetes or similar) Comfort working independently in a small team with real ownership Skills & Expertise Expert SQL and Python, with strong software engineering habits: tests, code review and CI Warehouse and lake experience with real modelling: Iceberg or Delta on S3, Athena/Trino, Snowflake or BigQuery, and dbt An orchestrator in production (dbt, Airflow or Argo) and distributed processing (Spark or equivalent) AWS, Kubernetes (EKS), Helm and Terraform — you can debug a failing Glue job and a broken Helm release Additional Strengths Prior 0-to-1 platform ownership at a startup Experience working with research teams on generative models, or hands-on exposure to audio, video, image or 3D data FinOps and cloud cost reporting Familiarity with SOC 2 or similar compliance requirements for data access Benefits & Compensation Health coverage for you and your family.

Choose from PPO and HMO plans, including select plans where Stability AI covers 100% of premiums for you and your eligible dependents. HSA and FSA accounts to set aside pre-tax dollars for healthcare and other eligible expenses. Company-paid life insurance, with the option to add voluntary coverage for yourself, your spouse, and your children. Short- and long-term disability coverage, to protect part of your income if illness or injury keeps you from working.

401(k) with company match of up to 4%. Paid parental leave to support you as your family grows. Flexible paid time off, plus paid company holidays. The equipment you need to do your best work, provided by Stability AI. At Stability AI, we aim to pay fairly and competitively, and we believe you should know what a role pays before you invest time in getting to know us. The annual base salary range for this role is USD 175,500 - USD 230,000 USD.

It reflects our good-faith expectation for the role as posted and applies to candidates hired within the United States. Where you fall within that range depends on the depth and relevance of your experience, your skills, and how you perform in our interview process. Because great candidates don’t always map neatly to a single level, we may also consider someone for a level above or below the one posted. If we do, the range will be adjusted to match, and we’ll talk it through with you openly.

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Source listing: greenhouse_stabilityai

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