Senior GenAI Software Engineer
New
Based in United StatesFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 5+ years
- Required Skills
- PythonJavascriptTypeScriptA/B testingGenerative AI
Requirements
- 5+ years of relevant software engineering experience, including strong foundations in system design, production debugging, and scalable backend architecture.
- Proven experience building and shipping LLM-powered or GenAI systems into production, with a deep understanding of real-world failure modes and system tradeoffs.
- Strong programming skills in Python for AI/agent development and proficiency in JavaScript/TypeScript for frontend, creative tooling, or interactive applications.
- Hands-on experience with multimodal AI systems, including image and/or video generation models, diffusion models, or related generative technologies.
- Strong understanding of evaluation methodologies for AI systems, including offline metrics, human evaluation, and experiment design (A/B testing).
- Ability to design systems that balance model intelligence with deterministic logic, including tooling, context engineering, and system safeguards.
- Excellent communication skills with the ability to collaborate across technical and non-technical teams in ambiguous, fast-evolving environments.
Responsibilities
- Architect and deliver end-to-end GenAI systems for ad creative generation, including multimodal pipelines, code generation components, and interactive playable ad experiences in production environments.
- Rapidly prototype experimental AI solutions, validate performance against real creative use cases, and transition successful prototypes into scalable, production-ready systems.
- Design robust evaluation frameworks for generative outputs, including human-in-the-loop review systems, A/B testing frameworks, and automated quality assessment metrics.
- Build and maintain AI agent systems that optimize creative workflows, incorporating guardrails, fallback mechanisms, and quality control layers to manage model variability.
- Partner closely with creative strategists, product managers, and cross-functional engineering teams to translate domain expertise into scalable AI-driven systems.
- Research emerging developments in LLMs, vision models, diffusion models, and multimodal AI, and translate insights into new product initiatives and technical capabilities.
- Mentor engineers and contribute to engineering best practices, fostering a culture of experimentation, feedback, and technical excellence across the team.
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