Stealth Startup (AI)
Automation Engineer [32616]
Stealth Startup (AI), San Francisco, California, United States, 94199
Company Overview
We are redefining how enterprises prepare and optimize data at the most fundamental layer of the AI stack. Our technology operates deep in the data infrastructure layer, making data efficient, secure, and ready for scale.
We eliminate the hidden inefficiencies in modern data platforms—slashing storage and compute costs, accelerating pipelines, and boosting platform efficiency. The result: 60%+ lower storage costs, up to 60% lower compute spend, 3× faster data processing, and 20% overall efficiency gains.
Why It Matters Massive data should fuel innovation, not drain budgets. We remove the bottlenecks holding AI and analytics back—making data lighter, faster, and smarter so teams can ship breakthroughs, not babysit storage and compute bills.
Who We Are
World-renowned researchers in compression, information theory, and data systems
Elite engineers from Google, Pure Storage, Cohesity, and top cloud teams
Enterprise sellers who turn ROI into seven‑figure wins.
Powered by Investors & Customers $65M+ raised from NEA, Bain Capital, A* Capital, and operators behind Okta, Eventbrite, Tesla, and Databricks. Our platform already processes hundreds of petabytes for industry leaders.
Mission We’re building the default data substrate for AI, and a generational company built to endure.
Job Summary We are looking for an
SDET (QA Automation Engineer)
with hands‑on experience in backend testing using
Python
and working knowledge of
Kubernetes ,
Apache Spark , and
data lake architectures . In this role, you’ll collaborate with engineers across product and platform teams to ensure the quality of services powering our data‑driven AI infrastructure.
What You’ll Do
Design, develop, and maintain automated test scripts using industry‑standard tools and frameworks
Create and execute comprehensive test plans for APIs and big data applications
Implement automated regression, functional, integration, and performance testing
Develop and maintain test data management strategies
Create reusable test components and maintain test automation frameworks
Perform manual testing when required, including exploratory and usability testing
Identify, document, and track software defects using bug tracking tools
Collaborate with developers to reproduce and resolve issues
Conduct root cause analysis for test failures and production issues
Ensure compliance with quality standards and testing methodologies
Integrate automated tests into CI/CD pipelines
Provide testing estimates and ensure timely delivery of testing milestones
Continuously evaluate and implement new testing tools and methodologies
Qualifications
7-10 years of experience in backend test automation with a strong focus on Python.
Experience working in distributed systems, data engineering, or infrastructure‑heavy environments.
Familiarity with Apache Spark and related big data technologies.
Hands‑on experience with Kubernetes for container orchestration and test environment setup.
Solid understanding of data lakes, including experience with formats (Parquet, ORC), storage layers, or lakehouse platforms.
Experience with REST API testing, data validation, and large‑scale test data management.
Comfortable with tools like Pytest, Postman, Git, Jenkins, or similar CI/CD tools.
Strong debugging and problem‑solving skills in cloud‑native environments.
Background in data infrastructure, machine learning pipelines, or systems programming.
Familiarity with distributed systems concepts (e.g., compression, storage tiering, streaming data).
Experience working in a startup or fast‑paced technical environment.
Experience with Kubernetes, Terraform, or infrastructure as code tools.
Comfort with performance tuning, benchmarking, and systems observability.
Work hands‑on with petabyte‑scale datasets, design performant systems and compression algorithms that matter.
Partner with elite engineers from companies like Google, Tesla, and Palantir on complex issues.
Tackle meaningful problems that push the boundaries of data infrastructure and AI.
Benefits
Unlimited PTO, flexible hybrid setup, competitive compensation, full health coverage.
Immigration sponsorship and counseling.
Premium health, dental, and vision coverage.
Flexible remote work, quarterly recharge days, annual team off‑sites.
Budget for learning, development, and conferences.
Uncapped commissions and meaningful equity.
Equal Opportunity Employer We celebrate diversity and are committed to creating an inclusive environment for all employees.
We do not discriminate on the basis of race, religion, color, gender expression or identity, sexual orientation, national origin, citizenship, age, marital status, veteran status, disability status, or any other characteristic protected by law.
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We eliminate the hidden inefficiencies in modern data platforms—slashing storage and compute costs, accelerating pipelines, and boosting platform efficiency. The result: 60%+ lower storage costs, up to 60% lower compute spend, 3× faster data processing, and 20% overall efficiency gains.
Why It Matters Massive data should fuel innovation, not drain budgets. We remove the bottlenecks holding AI and analytics back—making data lighter, faster, and smarter so teams can ship breakthroughs, not babysit storage and compute bills.
Who We Are
World-renowned researchers in compression, information theory, and data systems
Elite engineers from Google, Pure Storage, Cohesity, and top cloud teams
Enterprise sellers who turn ROI into seven‑figure wins.
Powered by Investors & Customers $65M+ raised from NEA, Bain Capital, A* Capital, and operators behind Okta, Eventbrite, Tesla, and Databricks. Our platform already processes hundreds of petabytes for industry leaders.
Mission We’re building the default data substrate for AI, and a generational company built to endure.
Job Summary We are looking for an
SDET (QA Automation Engineer)
with hands‑on experience in backend testing using
Python
and working knowledge of
Kubernetes ,
Apache Spark , and
data lake architectures . In this role, you’ll collaborate with engineers across product and platform teams to ensure the quality of services powering our data‑driven AI infrastructure.
What You’ll Do
Design, develop, and maintain automated test scripts using industry‑standard tools and frameworks
Create and execute comprehensive test plans for APIs and big data applications
Implement automated regression, functional, integration, and performance testing
Develop and maintain test data management strategies
Create reusable test components and maintain test automation frameworks
Perform manual testing when required, including exploratory and usability testing
Identify, document, and track software defects using bug tracking tools
Collaborate with developers to reproduce and resolve issues
Conduct root cause analysis for test failures and production issues
Ensure compliance with quality standards and testing methodologies
Integrate automated tests into CI/CD pipelines
Provide testing estimates and ensure timely delivery of testing milestones
Continuously evaluate and implement new testing tools and methodologies
Qualifications
7-10 years of experience in backend test automation with a strong focus on Python.
Experience working in distributed systems, data engineering, or infrastructure‑heavy environments.
Familiarity with Apache Spark and related big data technologies.
Hands‑on experience with Kubernetes for container orchestration and test environment setup.
Solid understanding of data lakes, including experience with formats (Parquet, ORC), storage layers, or lakehouse platforms.
Experience with REST API testing, data validation, and large‑scale test data management.
Comfortable with tools like Pytest, Postman, Git, Jenkins, or similar CI/CD tools.
Strong debugging and problem‑solving skills in cloud‑native environments.
Background in data infrastructure, machine learning pipelines, or systems programming.
Familiarity with distributed systems concepts (e.g., compression, storage tiering, streaming data).
Experience working in a startup or fast‑paced technical environment.
Experience with Kubernetes, Terraform, or infrastructure as code tools.
Comfort with performance tuning, benchmarking, and systems observability.
Work hands‑on with petabyte‑scale datasets, design performant systems and compression algorithms that matter.
Partner with elite engineers from companies like Google, Tesla, and Palantir on complex issues.
Tackle meaningful problems that push the boundaries of data infrastructure and AI.
Benefits
Unlimited PTO, flexible hybrid setup, competitive compensation, full health coverage.
Immigration sponsorship and counseling.
Premium health, dental, and vision coverage.
Flexible remote work, quarterly recharge days, annual team off‑sites.
Budget for learning, development, and conferences.
Uncapped commissions and meaningful equity.
Equal Opportunity Employer We celebrate diversity and are committed to creating an inclusive environment for all employees.
We do not discriminate on the basis of race, religion, color, gender expression or identity, sexual orientation, national origin, citizenship, age, marital status, veteran status, disability status, or any other characteristic protected by law.
#J-18808-Ljbffr