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Full-Stack Engineer – Automation, AI Evaluation

Job not on LinkedIn

🕒 September 21

🇮🇳 India – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 QA Automation Engineer

Where this job comes from

Posted on Streamhub's careers page, not through a job board

First seen by Remote Rocketship September 21

Still open on Streamhub's site. Checked 1 hour ago.

Logo of Streamhub

Streamhub

11 - 50 employees

💼 Consulting

📣 Marketing

📱 Media

Consulting • Marketing • Media

Streamhub is a video analytics startup providing audience and content insights for media companies. It’s made for video from the ground up and provides a one-stop shop of video data across all devices and platforms. Streamhub strives to answer how content impacts the engagement and loyalty of audiences on VOD and Live services, helping companies with insights into talent casting, program scheduling, traffic sources for attracting quality audiences, and understanding audience churn. With a focus on making big data relevant for the online TV industry, Streamhub aims to become the leader in video analytics for media companies worldwide.

📋 Description

• Build and ship backend services and APIs using Python and/or Node/TypeScript against large-scale data systems • Contribute to data modelling and transformation logic on the Snowflake-based platform • Build and extend React front-end modules for customer-facing analytics • Take features end to end through design, implementation, testing, review, release, and post-release verification • Own and evolve API and web automation frameworks • Design automated validation for ETL pipelines, including reconciliation, schema and contract checks, aggregation, and business-rule verification • Write advanced SQL for data integrity and reconciliation testing • Integrate quality gates into CI/CD to catch regressions, schema breaks, and contract violations before deployment • Investigate data quality issues end to end, fix root causes, and automate preventative checks • Use AI-assisted development tools for implementation, test generation, and coverage expansion • Build evaluation harnesses for AI and agent-based features • Apply AI to anomaly, regression, and data-drift detection and root-cause analysis • Work in a product squad, ship to customers, and participate in feature design conversations

🎯 Requirements

• 4+ years building software • Demonstrable backend development experience, including designing and shipping services and APIs • Strong hands-on coding in Python or JavaScript/TypeScript • Working front-end capability in React • Advanced SQL and comfort working with large datasets, warehouses, and ETL pipelines • Built or substantially owned a test automation framework from scratch, including structure, fixtures, test data management, parallelisation, and reporting • Hands-on API automation experience covering contract, integration, and end-to-end testing • Web UI automation experience with Playwright, Cypress, Selenium, or similar • Ability to define test strategies across unit, integration, and E2E testing • Experience integrating automated suites into CI/CD as enforcing quality gates • Experience validating data correctness at scale, including reconciliation, aggregation and transformation checks, and schema and contract validation • Strong debugging and root-cause analysis skills • Fluency with AI-assisted development tools and judgement to assess their output • Ownership mindset and ability to scope ambiguous problems, decide what to automate, and follow work through release • Nice to have: experience testing or evaluating LLM/agent-based features • Nice to have: performance testing with JMeter, Gatling, or k6 • Nice to have: Snowflake, dbt, or comparable modern data-stack experience • Nice to have: familiarity with distributed data systems, event-driven architectures, or adtech/media measurement • Nice to have: additional languages such as Java or Scala

🏖️ Benefits

• Competitive salary, benchmarked against full-stack engineering bands rather than QA bands • Immense learning and exposure to niche data technologies • Handling TBs of data • Work with an open, diverse, and autonomous team • Entrepreneurial team culture • Flexible timing

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