Senior Software Engineer II (AI Native)
New
J
JobgetherConsumer Technology
Fully remote work opportunity for candidates based in Canada or the United StatesFull-TimeSenior
SalaryCanadian salary range of $171,500–$201,000 CAD for candidates based in Canada.
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Job Details
- Experience
- 5+ years of professional experience
- Required Skills
- AWSAndroidJavaKafkaKotlinSpring BootSwiftPrompt EngineeringLLMiOS
Requirements
- 5+ years of professional experience building and operating high-quality, consumer-scale software or services.
- At least 1 year of hands-on experience prompting, evaluating, and building with large language models or AI-based development technologies.
- Strong full-stack capabilities spanning backend services and native mobile development, with experience in iOS and/or Android.
- Experience with technologies such as Java, Spring Boot, Kafka, Kafka Streams, AWS, Swift, Kotlin, or comparable modern backend, cloud, and mobile technologies.
- Deep understanding of agentic development workflows, prompt engineering, context management, and MCP/function calling.
- Demonstrated ability to use AI tooling as a substantive engineering partner.
- Strong ownership mindset, with the ability to identify problems independently and follow solutions through development, production, and measurable customer impact.
- Strong communication and collaboration skills.
- Interest in defining and improving AI-native engineering practices.
- Strong empathy for end users and the ability to translate real human needs into thoughtful technical solutions.
- Experience with performance, reliability, accessibility, incident response, and production operations.
- Bachelor's degree in a technical field or equivalent professional experience.
Responsibilities
- Design, build, and operate end-to-end product features across backend services, APIs, and native iOS and Android experiences.
- Work across Java, Spring Boot, Kafka, Kafka Streams, AWS, Swift, Kotlin, and related cloud-native technologies as required by the product.
- Use AI coding assistants and agentic workflows as first-class engineering tools for analysis, specification, implementation, testing, refactoring, codebase navigation, and documentation.
- Help establish and document AI-native engineering practices, creating playbooks and workflows that can be adopted across the wider engineering organization.
- Collaborate closely with product managers, designers, and platform engineers to turn complex user needs into reliable, scalable, and accessible solutions.
- Own the complete lifecycle of the systems and features you build, from initial implementation through production monitoring, incident response, and on-call support.
- Contribute to architectural decisions, technical standards, code reviews, and continuous improvement initiatives.
- Apply AI-assisted development techniques to increase engineering leverage while maintaining strong quality, security, reliability, and accountability standards.
- Mentor other engineers and share effective AI workflows, prompting strategies, development practices, and technical approaches.
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