Senior Software Engineer - AI Enablement
Senior Software Engineer - AI Enablement
Posted 8 days ago
SENIORITY
Lead
About the role
- Serves in a leadership capacity as an individual contributor for carrying out software development in PythonBuilds tools, extensions, and systems that help engineers effectively harness AI models and platforms
- Develops AI plugins, skills, and agents that connect AI with Garmin's engineering tools and knowledge bases
- Creates repeatable patterns for configuring and applying AI in everyday engineering
- Builds and maintains systems for sharing and updating AI plugins across Garmin
- Develops benchmarks to differentiate AI models based on cost versus performance
- Stewards the influx of AI coding platform features, assessing risks and guiding how features are enabled, configured, and used
- Researches emerging AI techniques and prototypes promising ideas
- Creates and curates training, demos, and practical guidance that help engineers use AI effectively
- Partners with engineering teams to understand their needs, improve solutions, and share what works
- Bachelor's Degree in Computer Science, Engineering, Mathematics, Physics or related field AND a minimum of 5 years relevant experience, or an equivalent combination of education and experience
- Excellent academics (cumulative GPA greater than or equal to 3.0 as a general rule)
- Proficiency in Python and a working knowledge of C/C++Experience designing, building, and maintaining software systems
- Experience with software development quality methodologies such as design review, code reviews, continuous integration, regression testing and static code analysis
- Demonstrated strong and effective verbal, written and interpersonal communication skills
- Demonstrated ability to collaborate effectively and contribute to a positive team environment
- Ability to decompose functional requirements into well-defined tasks while balancing quality, quantity, and complexity in work output
- Demonstrated capability to offer peer technical assessments in areas of expertise, new technologies and software designs
- Ability to prioritize work, solve complex problems, and lead in a changing environment
- Experience evaluating AI-powered systems against defined criteria for correctness, reliability, or task performance
- Firm grasp of how LLM-based systems use prompts, context, and tools, including their limitations and common failure modes
- Experience integrating AI APIs into production applications or engineering tools
- Experience and/or working knowledge of the SDLC of embedded software development
- Experience designing context and prompts that shape AI systems to perform effectively within token and context limits
- Familiarity with retrieval techniques such as embeddings, document indexing, semantic search, RAG, or similar approaches
- Experience building AI agents that use tools and carry out multi-step workflows
- Experience building AI workflows with persistent memory and event-driven automation such as hooks that manage context, run validations, or trigger follow-up tasks
- A disciplined approach to testing AI-generated outputs and identifying errors or limitations
- Experience building evaluation frameworks that track AI quality and detect changes in behavior over time
- Experience creating shared developer tools, plugins, or technical training
Before you apply
Applying takes about a minute. These four things decide how fast it moves after that.
Your profile is current
It's what we read first. Occupations, seniority and locations matter more than a long history.
Two examples you can talk through
Not a portfolio — just two pieces of work where you can explain the decisions and what you'd change.
A number in mind
What you're on now and what would make you move. We negotiate better when we know both.
Your notice period
Employers plan around it, and it's the question that stalls offers most often.
Once you apply, someone reads it and calls you before anything reaches the employer — usually within two working days.
