Automation Engineer [32616]

Get AI-powered advice on this job and more exclusive features. The company is redefining how enterprises prepare and optimize data at the most fundamental layer of the AI stack—where raw information becomes usable intelligence. 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 World-Class 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 Our Mission: We’re building the default data substrate for AI, and a generational company built to endure. Job Summary We are looking for a 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 What We’re Looking For 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 what’s possible in data infrastructure and AI Outcome-driven culture : Low ego, high trust, customer-obsessed. We scaled to multimillion-dollar ARR without a dedicated sales team—just product pull and ROI. Generous benefits : Unlimited PTO, flexible hybrid setup, competitive compensation, full health coverage Backed by top-tier VCs with strong runway and bold ambitions. Highly competitive compensation with uncapped commissions and meaningful equity Immigration sponsorship and counseling Premium health, dental, and vision coverage Flexible remote work and unlimited PTO Quarterly recharge days and annual team off-sites Budget for learning, development, and conferences The company celebrates diversity and is 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. EEO statements preserved above. #J-18808-Ljbffr Stealth Startup (AI)