AI Enablement Engineer for Mobile Apps

We are looking for a role whose main goal is to drive the adoption of AI-assisted engineering practices across one of our biggest client mobile applications ecosystem improving developer productivity QA automation CI/CD workflows operational efficiency integration quality and engineering standards. This role works closely with Engineering QA Architecture Platform and DevOps teams ensuring AI initiatives remain aligned with platform standards governance security and enterprise delivery roadmaps.

Main responsibilities

• Evaluate and promote AI-assisted engineering tools and workflows aligned with enterprise standards and architecture principles.
• Collaborate with Mobile Platform team QA and DevOps teams to identify automation and productivity opportunities across frontend backend APIs integrations and CI/CD pipelines
• Define and implement AI-assisted engineering practices across mobile development QA and delivery pipelines.
• Integrate AI-assisted practices into shared frameworks SDKs testing utilities modular architectures and CI/CD tooling.
• Drive adoption of AI-assisted tools automation and engineering workflows across development teams.
• Support teams with best practices around AI-assisted development code review test generation documentation and automation.
• Define and track engineering productivity and QA metrics identifying opportunities for continuous improvement.
• Promote consistent adoption of AI-assisted practices across teams contributing to engineering governance and shared standards.

Qualifications :

• Bachelors degree in computer science Software Engineering or equivalent.
• Proven experience with AI-assisted software engineering workflows agents and modern development tooling.
• Experience developing mobile applications on iOS and/or Android platforms including modular architectures and shared platform development.
• Experience with QA automation device testing farms and CI/CD platforms such as GitHub Actions and Jenkins.
• Experience integrating automation testing and quality controls into engineering delivery pipelines.
• Ability to quickly understand existing engineering ecosystems and work effectively across multiple teams.
• Strong collaboration and communication skills in distributed engineering organizations
• Ability to train and support teams adopting new engineering practices tooling and workflows.

Additional Information :

Extra Skills

• Strong autonomy and ability to proactively identify opportunities and drive initiatives
• Strong collaboration and governance mindset with focus on consistency alignment and knowledge sharing across teams.
• Ability to drive adoption and influence engineering practices without direct authority.
• Familiarity with LLM-based automation and enterprise AI tooling evaluation/adoption.
• Experience improving developer experience engineering velocity release quality or automation maturity.

Remote Work :

No

Employment Type :

Full-time