About the Company : 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.
About the Role : 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 idóneo 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.
Responsibilities :
- Design and implement AI-powered solutions focused on: - Automated test failure triage — LLM + RAG pipeline classifying Report Portal failures (logs, stack traces, screenshots) into structured categories (PRODUCT_BUG, AUTOMATION_BUG, SYSTEM_ISSUE) using AWS Bedrock + Claude - AI-based Change-Based Testing (CBT) — LLM-driven test case selection using semantic similarity between code changes and test coverage - AI test case generation from feature specs, Jira tickets, and Confluence documentation - Build and maintain end-to-end RAG pipelines: document ingestion → chunking → embedding → Open Search 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 / Ui Automator2) for Android TV platforms - Develop and maintain functional, regression, NFR,



and CBT test suites - Triage and resolve test failures in Report Portal; integrate AI triage results with QMetry (QTM4 J) - 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
Qualifications :
- Education details
Required Skills :
- AWS Bedrock — hands-on: model access, Knowledge Bases, Lambda integration (primary AI platform) - AI agents & Agentic tooling — practical knowledge of designing and operating AI agents, including agentic workflows, reusable skills, rules/guardrails, commands, and multi-tool/multi-agent orchestration - RAG pipeline — end-to-end implementation: chunking, embedding, vector indexing, retrieval, generation - Prompt engineering — zero-shot, few-shot, chain-of-thought, structured output (JSON mode), multi-turn - Vector databases — working knowledge of Open Search, Pinecone, or Faiss; understands vector vs. graph DB difference - LLM guardrails — input/output filtering, hallucination mitigation strategies - Fine-tuning vs. RAG — ability to reason through which approach fits a given problem - LLM orchestration — Lang Chain, Lang Graph, or Llama Index - Embeddings — understands semantic similarity; experience with Amazon Titan Embed or equivalent - Python — for Lambda functions, AI pipeline scripting, and data processing - Java — 3+ years of hands-on test automation development - Appium / Ui Automator2 — mobile/Android UI automation - Android / ADB — device management, test execution - Report Portal or equivalent test reporting tool - REST API — concepts and hands-on usage - Jenkins / CI-CD — pipeline debugging and integration - AWS — S3, Lambda, API Gateway, IAM, Open Search Serverless - Docker — containerized test execution environments
Preferred Skills :

📌 Ingeniero de inteligencia artificial (Ciudad de México)
🏢 Luxoft Mexico
📍 Ciudad de México