[Hiring] Applied AI Engineer @Bask Health

Role Description

We're looking for an Applied AI Engineer, Patient Experience to help build intelligent, reliable, and intuitive AI-powered features across Bask Health's patient-facing applications. You'll help develop AI capabilities that make these interactions easier to navigate while maintaining appropriate privacy, reliability, and clinical safeguards.

This is a hands-on product engineering role focused on applying existing AI models and modern development tools to real software problems. Your work may include:

• AI-assisted patient navigation
• Intelligent explanations of administrative workflows
• Contextual help and information retrieval
• Automation that reduces repetitive steps for patients and internal teams

You'll collaborate with product managers, frontend engineers, backend engineers, and senior AI engineers to turn product requirements into working features. Responsibilities include:

• Build and maintain AI-powered features across Bask Health's patient-facing applications
• Integrate large language models into existing patient workflows and software services
• Develop AI-assisted experiences that help patients navigate onboarding and account-related processes
• Build contextual assistance features for questionnaires, patient portals, and other approved workflows
• Implement AI-powered information retrieval and knowledge-grounded responses
• Develop backend services and APIs that support patient-facing AI functionality
• Work with frontend engineers to integrate AI capabilities into intuitive application interfaces
• Implement prompt templates, structured outputs, and model interaction logic
• Develop retrieval-augmented generation pipelines for approved informational use cases
• Connect AI applications to internal services and approved data sources
• Build tool-calling functionality with appropriate permissions and validation
• Implement safeguards that prevent AI systems from performing unauthorized actions
• Develop automated tests for AI features and supporting application logic
• Evaluate model outputs for accuracy, relevance, consistency, and usefulness
• Investigate hallucinations, incorrect responses, and unexpected model behavior
• Improve prompts, retrieval configurations, and application logic based on evaluation results
• Work with senior engineers to select appropriate models and integration approaches
• Implement logging, tracing, and monitoring for AI-powered services
• Help improve response latency, reliability, and operational efficiency
• Handle model API failures, timeouts, retries, and fallback behavior
• Support privacy-conscious handling of sensitive patient information
• Collaborate with product and clinical stakeholders to understand workflow requirements
• Ensure patient-facing AI features respect approved clinical and operational boundaries
• Participate in code reviews, technical discussions, and architecture planning
• Use AI-assisted development tools to improve engineering productivity while reviewing generated code carefully
• Troubleshoot production issues and implement reliable fixes
• Contribute to reusable AI components, libraries, and internal engineering tools
• Own assigned features from implementation through testing, deployment, and ongoing improvement

Qualifications

• 3+ years of professional software engineering experience, preferably including applied AI or machine learning application development
• Experience building and deploying production software applications
• Strong programming skills in TypeScript, JavaScript, Python, or comparable languages used in AI application development
• Experience integrating third-party APIs into production applications
• Familiarity with large language models and modern generative AI capabilities
• Hands-on experience developing AI-powered features or applications
• Understanding of prompt engineering and structured model outputs
• Familiarity with model APIs and common LLM integration patterns
• Experience developing backend services and REST or comparable APIs
• Understanding of asynchronous programming and external service integrations
• Familiarity with relational databases and application data models
• Experience writing maintainable, well-tested production code
• Understanding of software testing, debugging, and code review practices
• Familiarity with Git and collaborative software development workflows
• Ability to troubleshoot API failures, integration issues, and unexpected application behavior
• Understanding of authentication, authorization, and secure API design
• Familiarity with cloud-based application deployment
• Ability to evaluate AI outputs and identify obvious quality or reliability problems
• Understanding of the limitations of large language models
• Familiarity with logging, monitoring, and production diagnostics
• Ability to collaborate effectively with product managers, designers, and other engineers
• Experience translating product requirements into working software features
• Strong problem-solving skills and attention to detail
• Ability to independently deliver assigned engineering projects
• Clear written and verbal communication skills

Nice to Have

• Experience building AI-powered features for healthcare, telehealth, or patient-facing applications
• Familiarity with OpenAI, Anthropic, or comparable model APIs
• Experience with retrieval-augmented generation architectures
• Familiarity with embeddings, semantic search, and vector databases
• Experience with AI agent frameworks or tool-calling applications
• Familiarity with structured output validation and schema-based model responses
• Experience with TypeScript and Node.js backend development
• Experience with React or Next.js applications
• Familiarity with tRPC, Prisma, Drizzle, or similar application development tools
• Experience working with AWS services or serverless architectures
• Familiarity with AI evaluation frameworks and automated model testing
• Experience implementing prompt versioning or AI configuration management
• Familiarity with model observability, tracing, and error analysis
• Experience improving AI response latency and API usage costs
• Understanding of HIPAA and healthcare data privacy considerations
• Experience designing human-in-the-loop AI workflows
• Familiarity with patient onboarding, intake questionnaires, or healthcare messaging workflows
• Experience building internal tools that support customer-facing applications
• Experience with feature flags, experimentation, and incremental product rollouts
• Experience using AI-assisted development tools such as Cursor or Claude Code