Experience: 5+ Years
Location: Plano, TX
Work Model: Hybrid
Employment Type: Full-Time
About the RoleWe are looking for a highly experienced
AI Android Software Engineer - Reliability to join our engineering team. This role combines strong software engineering and production debugging expertise with
AI-driven tools, agent frameworks, and automation to accelerate issue diagnosis, reduce resolution time, and improve overall system reliability.
The ideal candidate will have strong hands-on experience with
Android, Kotlin, C++, and .NET/C#, along with a proven ability to troubleshoot complex production issues using logs, telemetry, and root-cause analysis.
You will leverage
AI agents, intelligent log analysis, automated root-cause workflows, RAG-based solutions, and AI-assisted development tools to reduce repetitive debugging efforts, improve defect triage, and proactively identify reliability risks.
This role sits at the intersection of
Android Software Engineering, Production Reliability, and Applied AI Automation.Key Responsibilities- Diagnose and resolve complex production issues across Android, C++, Kotlin, React Native, and .NET systems using logs, telemetry, and AI-assisted analysis.
- Design and improve AI-enabled log analysis and incident-triage workflows to accelerate root-cause identification.
- Leverage AI-assisted development tools to efficiently generate, test, validate, and implement code fixes.
- Identify repetitive break/fix patterns and develop AI-driven automation to reduce manual debugging efforts.
- Integrate AI-supported diagnostics and automation into CI/CD pipelines and defect-tracking systems.
- Develop durable fixes that reduce recurring incidents and improve overall system reliability.
- Build and refine Retrieval-Augmented Generation (RAG) workflows to surface historical incident information and identify recurring patterns.
- Analyze production defects and recommend systemic improvements and automation opportunities.
- Document resolutions, troubleshooting approaches, and automation improvements to expand AI-assisted resolution capabilities.
- Collaborate closely with engineering and operations teams to improve production stability and reduce Mean Time to Resolution (MTTR).
Required Skills & Qualifications- 5+ years of professional software engineering experience, including hands-on experience in production environments.
- Strong hands-on experience with Android and Kotlin development.
- Proficiency in C++ and C#/.NET.
- Strong debugging, troubleshooting, and root-cause analysis skills across multiple platforms.
- Experience analyzing application logs, telemetry, production defects, and performance issues.
- Hands-on experience using AI-assisted development tools, such as GitHub Copilot or LLM-based engineering workflows.
- Practical experience building or contributing to AI-driven automation workflows, including log analysis, retrieval-based systems, or task automation.
- Understanding of RESTful APIs, multithreading, memory management, and performance troubleshooting.
- Experience with Git/version control and CI/CD pipelines for safely deploying and validating fixes.
- Ability to identify recurring defects and translate them into automation or systemic reliability improvements.
- Strong communication and collaboration skills with the ability to work across engineering and operations teams.
Nice-to-Have Skills- Experience with Point-of-Sale (POS) solutions, particularly within hospitality or restaurant technology.
- Familiarity with EMV payments and payment-processing systems.
- Experience with Digital Content Management platforms and workflows.
- Exposure to embedded systems or hardware integration.
- Knowledge of cloud platforms such as AWS or Azure and backend services.
- Familiarity with Agile methodologies and ticketing systems such as Jira.
Ideal Candidate ProfileThe ideal candidate is a
hands-on Android/software engineer with 5+ years of experience, strong production debugging expertise, and practical experience using AI tools and automation to improve engineering and reliability workflows.
