[Hiring] Head of Applied AI @Bask Health

Role Description

We're looking for a Head of Applied AI to lead the technical development of AI-powered capabilities across Bask Health's platform. This role combines hands-on AI engineering, technical leadership, and product-focused problem-solving. You'll help define how artificial intelligence is integrated into Bask's applications, guide the architecture of production AI systems, and work closely with engineering and product teams to turn promising AI capabilities into reliable software.

Your work may involve:

• Merchant-facing AI tools
• Patient experience improvements
• Internal operational automation
• Search and discovery
• Intelligent features that help users navigate complex workflows

You'll be responsible for establishing strong engineering practices around:

• Model evaluation
• Reliability
• Performance
• Security
• Observability

This is a hands-on technical leadership role, not a purely strategic or research-focused position. You'll contribute to architecture, review implementations, prototype new capabilities, and help engineers solve challenging technical problems while guiding the broader direction of applied AI development.

You'll collaborate with company leadership, product managers, engineers, and operational teams to identify high-value opportunities and prioritize AI initiatives based on their practical impact.

What You'll Do

• Lead the technical direction and development of applied AI capabilities across Bask Health's platform.
• Define the architecture and engineering standards for production AI applications.
• Guide the design and implementation of systems powered by large language models and machine learning.
• Work closely with company leadership, product managers, and engineers to identify high-impact AI opportunities.
• Translate product and business requirements into practical AI engineering initiatives.
• Lead the development of merchant-facing AI features, intelligent assistants, and automation tools.
• Guide AI applications supporting patient experiences and internal operational workflows.
• Design scalable systems for integrating AI models into existing software applications.
• Evaluate model providers, APIs, frameworks, and infrastructure for production use.
• Establish engineering practices for prompt management, model evaluation, and output validation.
• Develop approaches for measuring AI accuracy, usefulness, latency, cost, and reliability.
• Guide the implementation of retrieval-augmented generation, tool calling, and agentic workflows where appropriate.
• Establish safeguards and human-review mechanisms for sensitive AI-assisted workflows.
• Ensure AI systems are designed with appropriate privacy, security, and access controls.
• Work with backend and platform engineers to integrate AI services into production architecture.
• Define standards for monitoring, logging, troubleshooting, and observability across AI applications.
• Identify opportunities to improve model performance and reduce unnecessary inference costs.
• Lead technical investigations into AI system failures, unreliable outputs, and integration challenges.
• Contribute hands-on code, prototypes, and architectural improvements for complex AI initiatives.
• Review technical designs and provide guidance on implementation decisions.
• Mentor engineers working on AI applications, model integrations, and machine learning systems.
• Help establish reusable AI infrastructure, services, and development patterns.
• Collaborate with product teams to evaluate AI feature performance and user feedback.
• Prioritize engineering investments that improve the reliability and scalability of AI capabilities.
• Guide experimentation with emerging AI technologies while maintaining production engineering standards.
• Support technical planning, project execution, and cross-functional coordination for AI initiatives.
• Help build a culture of practical experimentation, technical ownership, and continuous improvement.
• Take responsibility for the technical quality and long-term maintainability of Bask's applied AI systems.

Qualifications

• 8+ years of professional experience in software engineering, machine learning engineering, AI engineering, or a comparable technical discipline.
• 3+ years of experience leading engineering teams, major technical initiatives, or complex AI projects.
• Demonstrated experience building and deploying AI-powered applications in production.
• Strong understanding of large language models and practical LLM application development.
• Hands-on experience integrating AI models through APIs or model-serving infrastructure.
• Strong programming skills in Python, TypeScript, or comparable production engineering languages.
• Experience designing scalable backend services and distributed application architectures.
• Strong understanding of retrieval-augmented generation, tool calling, and AI workflow orchestration.
• Experience evaluating model outputs and measuring AI system performance.
• Understanding of prompt engineering, structured outputs, and output validation.
• Experience designing systems that balance model quality, latency, reliability, and cost.
• Familiarity with cloud infrastructure and production deployment practices.
• Strong understanding of software architecture, APIs, and system integrations.
• Experience establishing engineering standards and reviewing complex technical designs.
• Familiarity with observability, monitoring, and incident investigation for production services.
• Understanding of application security, data privacy, and responsible AI implementation.
• Experience designing fallback behavior and safeguards for unreliable model outputs.
• Ability to evaluate new AI technologies and make practical technical recommendations.
• Experience collaborating with product managers and business stakeholders.
• Strong technical leadership and engineering mentorship skills.
• Ability to communicate complex technical concepts to both technical and nontechnical audiences.
• Strong analytical and problem-solving abilities.
• Experience prioritizing technical initiatives and balancing competing engineering requirements.
• Willingness to remain hands-on with architecture, prototyping, and technical problem-solving.
• Comfort leading initiatives in a fast-moving, remote engineering environment.

Nice to Have

• Previous experience as a Head of AI, Applied AI Lead, Staff AI Engineer, or Engineering Manager for AI systems.
• Experience leading teams responsible for LLM-powered product development.
• Familiarity with OpenAI, Anthropic, or comparable model providers.
• Experience with LangChain, LangGraph, or comparable AI orchestration frameworks.
• Experience developing AI agents and multi-step tool-using workflows.
• Familiarity with vector databases, embeddings, and semantic search.
• Experience building retrieval and personalization systems.
• Experience with model evaluation frameworks and automated quality testing.
• Familiarity with model fine-tuning, distillation, or model adaptation techniques.
• Experience with MLOps, model deployment, or machine learning infrastructure.
• Experience with AWS and serverless or containerized application architectures.
• Familiarity with event-driven systems and asynchronous processing.
• Experience developing AI-powered SaaS applications.
• Experience building merchant-facing copilots or intelligent workflow assistants.
• Familiarity with e-commerce, subscription platforms, or merchant operations.
• Experience developing healthcare or telehealth software.
• Understanding of HIPAA and healthcare data privacy considerations.
• Experience designing human-in-the-loop AI systems for sensitive workflows.
• Familiarity with AI governance, auditability, and production risk management.
• Experience using AI-assisted development tools such as Cursor or Claude Code.