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описание
Req. VR-123781
Luxoft is building and maintaining a large OTT platform test automation framework serving millions of customers across streaming TV platforms. The team develops a Java/Appium-based automation framework for Android TV devices and is expanding it with AI-powered tooling.
задачи
Design and implement AI-powered solutions for automated test failure triage, AI-based Change-Based Testing, and AI test case generation;
Build and maintain end-to-end RAG pipelines from document ingestion through LLM response generation;
Develop AWS Lambda functions and API Gateway REST endpoints to integrate AI capabilities into CI/CD pipelines;
Apply prompt engineering best practices 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 using Appium and UiAutomator2 for Android TV platforms;
Develop and maintain functional, regression, NFR, and CBT test suites;
Triage and resolve test failures in ReportPortal and integrate AI triage results with QMetry (QTM4J);
Support CI/CD pipeline health through Nightly Build, RC, and release automation runs via Jenkins;
Contribute bug fixes, refactoring, and enhancements to the framework codebase;
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.
требования
Hands-on experience with AWS Bedrock, including model access, Knowledge Bases, and Lambda integration;
Practical knowledge of designing and operating AI agents, agentic workflows, reusable skills, rules, guardrails, commands, and multi-tool or multi-agent orchestration;
Experience implementing end-to-end RAG pipelines, including chunking, embedding, vector indexing, retrieval, and generation;
Knowledge of prompt engineering, including zero-shot, few-shot, chain-of-thought, structured JSON output, and multi-turn prompting;
Working knowledge of OpenSearch, Pinecone, or Faiss, including the difference between vector and graph databases;
Knowledge of LLM guardrails, input/output filtering, and hallucination mitigation strategies;
Ability to choose between fine-tuning and RAG for a given problem;
Experience with LangChain, LangGraph, or LlamaIndex;
Understanding of semantic similarity and experience with Amazon Titan Embed or an equivalent;
Python experience for Lambda functions, AI pipeline scripting, and data processing;
At least 3 years of hands-on Java test automation development;
Experience with Appium or UiAutomator2 for mobile or Android UI automation;
Experience with Android and ADB for device management and test execution;
Experience with ReportPortal or an equivalent test reporting tool;
Knowledge and hands-on experience with REST APIs;
Experience debugging and integrating Jenkins CI/CD pipelines;
Experience with AWS S3, Lambda, API Gateway, IAM, and OpenSearch Serverless;
Experience with Docker and containerized test execution environments;
English at C1 Advanced level;
Nice to have: Advanced Cursor IDE features, Android TV or STB/embedded device testing, QMetry (QTM4J), Streamlit, DSPy, AWS SageMaker, MLflow, Kotlin.
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