Senior Gen AI Developer
New
Fully remote, Eastern Standard Time (EST)Full-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 4+ years of overall software engineering experience, with at least 2+ years building and shipping production systems in product teams. 4+ years of hands-on technical experience writing production-quality code.
- Required Skills
- AWSPythonGCPTypeScriptAzureCI/CDGenerative AI
Requirements
- 4+ years of overall software engineering experience
- 2+ years building and shipping production systems in product teams
- 4+ years of hands-on technical experience writing production-quality code
- Strong software engineering fundamentals, including system design and scalable architecture
- Proficiency in Python
- Proficiency in TypeScript (or similar)
- Experience building APIs
- Experience building services
- Experience building data pipelines
- Experience with cloud platforms (AWS, GCP, or Azure)
- Experience with CI/CD pipelines
- Experience with automated testing
- Experience with observability
- An experimentation mindset
- Strong interest in learning and applying GenAI technologies in practical, production environments
- Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience
Responsibilities
- Contribute to building and scaling production-grade AI systems.
- Contribute to the delivery of GenAI-powered features.
- Collaborate closely with technical leads.
- Maintain technical quality, reliability, and scalability across a core product area.
- Build and improve AI-enabled product features from prototype to production.
- Build and maintain product features and supporting backend components, including services, integrations, and internal workflows.
- Write production-ready code and lightweight prototypes to validate ideas quickly.
- Create automated tests and proactively fix issues to keep releases stable.
- Support proof-of-concepts and experiments by setting up test cases, reviewing results, and improving areas where quality is weak.
- Document systems and workflows so others can run, maintain, and extend what you build.
- Translate business problems into clear AI tasks and implement end-to-end solutions.
- Prepare and maintain data and test cases used to measure output quality.
- Apply common AI application patterns such as prompting, using internal knowledge sources, and calling external tools or APIs.
- Measure quality using repeatable evaluation methods.
- Contribute to production readiness through versioning, monitoring, basic performance and cost awareness, and usage tracking.
- Follow privacy, security, and compliance requirements.
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