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Senior AI Developer (Automators)

Luxoft·Salary not specified

Primary stack

AWS BedrockDockerJenkinsPythonAWSAIRAGAPIAndroidJava

Nice to have's

Cursor IDE advanced featuresAndroid TV platformsQMetry (QTM4J)StreamlitDSPyAWS SageMaker / MLflowKotlin

Job description

About the Position

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 (Automators). 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.

Responsibilities

  • Design and implement AI-powered solutions focused on automated test failure triage, AI-based Change-Based Testing (CBT), and AI test case generation.
  • 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 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.

Requirements

  • 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 OpenSearch, 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 - LangChain, LangGraph, or LlamaIndex
  • 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 / UiAutomator2 - mobile/Android UI automation
  • Android / ADB - device management, test execution
  • ReportPortal 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, OpenSearch Serverless
  • Docker - containerized test execution environments

Nice to Have

  • Cursor IDE advanced features - .cursorrules, memory-bank context files, MCP server integration, and agentic triage workflows
  • Android TV platforms - STB / embedded device testing experience (Fire TV, Roku, or similar)
  • QMetry (QTM4J) - test management integrated with Jira
  • Streamlit - for building internal AI dashboards
  • DSPy - programmatic prompt optimization
  • AWS SageMaker / MLflow - model evaluation and experiment tracking
  • Kotlin - for tooling alongside Java

We Offer

  • Remote work from Mexico
  • Competitive salary
  • Opportunity to work with cutting-edge AI technologies
  • Collaborative and innovative team environment

About the Company

Luxoft is a global leader in digital transformation and technology services, empowering businesses to thrive in the digital era. Our expertise spans across various industries, delivering innovative solutions that drive growth and efficiency.

Apply now to join our team and contribute to the future of AI-driven test automation!

© Luxoft. This job description was sourced from the employer's public career page. TheJob is not the employer — we index the posting and route candidates to the source. All content rights and hiring decisions belong to the employer.

A provider of software development services and innovative IT solutions with a worldwide customer base consisting mainly of large multinational corporations.

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