Senior Generative AI Engineer

Summary

Join Virta Health as a Senior Generative AI Engineer and help shape the future of AI-powered coaching experiences. You will play a key role in evolving Virta's GPT-based chatbot into a powerful platform that supports coaches, engages members, and improves health outcomes. Collaborate with cross-functional teams to design and implement core infrastructure, contribute to the technical strategy for conversational AI, and write production-grade code. Mentor teammates, measure chatbot performance, and drive data-driven iteration. This role offers a unique opportunity to work at the intersection of GenAI, behavioral health, and mission-driven impact.

Requirements

• Experience with large language models (LLMs) such as OpenAI’s GPT, including prompt engineering and tuning for performance and engagement
• Strong software engineering skills, particularly in Python, with experience writing production-quality code
• Proven ability to design and build ML systems end-to-end, including experimentation frameworks, real-time pipelines, and monitoring infrastructure
• Experience deploying ML models in production environments, preferably on cloud platforms like Google Cloud Platform (GCP)
• Background in building or contributing to internal platforms/tools that are used across multiple teams or products
• Familiarity with experimentation methods, including A/B testing and evaluation of conversational systems
• Comfort working cross-functionally—collaborating closely with product managers, designers, and engineering stakeholders
• Strong communication and technical leadership skills, including mentoring other engineers and aligning on technical decisions within a larger leadership team
• Track record of using data to inform iteration, particularly with user-facing ML products where engagement and outcomes are key success metrics

Responsibilities

• Collaborate with cross-functional teams (product, design, engineering, and clinical experts) to evolve Viv, Virta’s GPT-powered chatbot, into a scalable platform
• Design and implement core infrastructure to support prompt orchestration, context management, experimentation, and evaluation at scale
• Contribute to the technical strategy for conversational AI—bringing a GenAI perspective to platform decisions, roadmap planning, and system architecture
• Write production-grade code and build robust ML systems that support continuous learning, monitoring, and iteration
• Mentor and guide teammates across disciplines, elevating engineering practices and GenAI fluency across the organization
• Measure and improve chatbot performance through data-driven iteration, focusing on member engagement, response quality, and outcome achievement

Preferred Qualifications

• Experience designing or optimizing conversational UX or working on chatbot platforms
• Familiarity with Retrieval-Augmented Generation (RAG) or similar methods for injecting user context into LLM prompts
• Prior work in health tech, digital coaching, or behavior change products
• Exposure to message routing systems or prioritization frameworks (e.g., trigger scoring, intent recognition, message sender selection)
• Experience with LLM-specific integrations like OpenAI's function calling, embeddings, or tool use patterns
• Knowledge of MLOps best practices, including CI/CD pipelines, container orchestration, and scalable model deployment
• Background in A/B testing for user engagement, particularly in GenAI or NLP-driven experiences
• Contributions to open-source GenAI tooling or external thought leadership (e.g., blog posts, talks, or research)
• Understanding of ethical and responsible AI practices, especially in user-facing applications

Benefits

• Remote work, flexible hours
• $220,439 - $276,101