Senior AI Developer (Automators)
Do uzgodnienia
Wymagania
- Java
- Appium
- Python
- AWS Bedrock
- LangChain
Opis stanowiska
We are building and maintaining one of the largest OTT platform test automation frameworks, serving millions of customers across streaming TV platforms. The team develops a Java/Appium-based automation framework for Android TV devices and is actively expanding it with AI-powered tooling.
We are looking for a Senior AI Developer. This is a hybrid role combining the design and development of AI-powered internal tools with hands-on test automation engineering skills. The ideal candidate is a software engineer who understands both QA automation and modern LLM/RAG systems — and can translate test engineering problems into practical AI solutions.
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Design and implement AI-powered solutions focused on:
o Automated test failure triage — LLM + RAG pipeline classifying ReportPortal failures (logs, stack traces, screenshots) into structured categories (PRODUCTBUG, AUTOMATIONBUG, SYSTEM_ISSUE) using AWS Bedrock + Claude
o AI-based Change-Based Testing (CBT) — LLM-driven test case selection using semantic similarity between code changes and test coverage
o AI test case generation from feature specs, Jira tickets, and Confluence documentation
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Build and maintain end-to-end RAG pipelines: document ingestion → chunking → embedding → OpenSearch Serverless vector store → retrieval → LLM response generation
- Develop AWS Lambda functions (Python 3.12) and API Gateway REST endpoints to integrate AI capabilities into CI/CD pipelines
- Apply prompt engineering best practices (system prompts, structured JSON output, guardrails) and drive continuous evaluation of LLM solution accuracy
- Use Cursor IDE with MCP integrations, agentic workflows, and context/rules files to accelerate test code generation and maintenance
- Write, maintain, and expand automated test suites in Java (Appium / UiAutomator2) for Android TV platforms
- Develop and maintain functional, regression, NFR, and CBT test suites
- Triage and resolve test failures in ReportPortal; integrate AI triage results with QMetry (QTM4J)
- Support CI/CD pipeline health — participate in Nightly Build, RC, and release automation runs via Jenkins
- Contribute to framework codebase improvements — bug fixes, refactoring, enhancements
- Participate in Kanban ceremonies and PI planning under the ART team
- Present AI solution demos to stakeholders and engineering leadership
- Document AI system architecture, RAG pipelines, and tools in Confluence
We are looking for a Senior AI Developer. This is a hybrid role combining the design and development of AI-powered internal tools with hands-on test automation engineering skills. The ideal candidate is a software engineer who understands both QA automation and modern LLM/RAG systems — and can translate test engineering problems into practical AI solutions.
-
Design and implement AI-powered solutions focused on:
o Automated test failure triage — LLM + RAG pipeline classifying ReportPortal failures (logs, stack traces, screenshots) into structured categories (PRODUCTBUG, AUTOMATIONBUG, SYSTEM_ISSUE) using AWS Bedrock + Claude
o AI-based Change-Based Testing (CBT) — LLM-driven test case selection using semantic similarity between code changes and test coverage
o AI test case generation from feature specs, Jira tickets, and Confluence documentation
-
Build and maintain end-to-end RAG pipelines: document ingestion → chunking → embedding → OpenSearch Serverless vector store → retrieval → LLM response generation
- Develop AWS Lambda functions (Python 3.12) and API Gateway REST endpoints to integrate AI capabilities into CI/CD pipelines
- Apply prompt engineering best practices (system prompts, structured JSON output, guardrails) and drive continuous evaluation of LLM solution accuracy
- Use Cursor IDE with MCP integrations, agentic workflows, and context/rules files to accelerate test code generation and maintenance
- Write, maintain, and expand automated test suites in Java (Appium / UiAutomator2) for Android TV platforms
- Develop and maintain functional, regression, NFR, and CBT test suites
- Triage and resolve test failures in ReportPortal; integrate AI triage results with QMetry (QTM4J)
- Support CI/CD pipeline health — participate in Nightly Build, RC, and release automation runs via Jenkins
- Contribute to framework codebase improvements — bug fixes, refactoring, enhancements
- Participate in Kanban ceremonies and PI planning under the ART team
- Present AI solution demos to stakeholders and engineering leadership
- Document AI system architecture, RAG pipelines, and tools in Confluence
🔍 Dekoder Ogłoszenia
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hybrid role combining the design and development of AI-powered internal tools with hands-on test automation engineering skills
Oczekuje się, że będziesz zarówno tworzyć zaawansowane narzędzia AI, jak i aktywnie zajmować się manualnym testowaniem i utrzymaniem istniejących skryptów automatyzujących.
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translate test engineering problems into practical AI solutions
Twoim głównym zadaniem będzie rozwiązywanie problemów z automatyzacją testów za pomocą AI, co może oznaczać konieczność głębokiego zanurzenia się w istniejący, być może niedoskonały, kod testowy.
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hands-on test automation engineering skills
Pomimo nacisku na AI, nadal będziesz musiał wykazywać się praktycznymi umiejętnościami w zakresie tworzenia i utrzymania skryptów automatyzujących testy, co może być czasochłonne.
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actively expanding it with AI-powered tooling
Projekt jest w fazie rozwoju, co oznacza, że możesz napotkać na nieustabilizowane rozwiązania i potrzebę ciągłego dostosowywania się do zmian.