Applied AI Engineer, Patient Experience

Bask Health

. Build and maintain AI-powered features across Bask Health's patient-facing applications .

Posted 11/12/2026full-timeRemote • United StatesMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and integrating AI-powered features within patient-facing applications, with a strong focus on backend services, API development, and collaboration with cross-functional teams. Proficient in evaluating AI outputs and ensuring compliance with healthcare data privacy standards.

Highest-signal resume keywords

AI-Powered Feature DevelopmentTypeScript ProgrammingAPI IntegrationLarge Language Model FamiliaritySoftware Testing and Debugging

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

TypeScriptJavaScriptPythonAI Application DevelopmentBackend Services DevelopmentREST API DevelopmentPrompt EngineeringAsynchronous ProgrammingSoftware TestingDebugging

Soft Skills

Problem-SolvingAttention to DetailClear CommunicationCollaboration

Tools & Technologies

GitCloud-Based DeploymentAI-Assisted Development ToolsLogging and Monitoring ToolsRelational Databases

Industry Keywords

HealthcarePatient-Facing ApplicationsHIPAA ComplianceTelehealthAI Evaluation Frameworks

Tech Stack

Tools & technologies

AWSCloudJavaScriptNext.jsNode.jsPythonReactTypeScript

About the role

Key responsibilities & impact

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 for patient onboarding and account-related processes
Build contextual assistance for questionnaires, patient portals, and approved workflows
Implement AI-powered information retrieval and knowledge-grounded responses
Develop backend services and APIs supporting patient-facing AI functionality
Collaborate with frontend engineers to integrate AI capabilities into 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 preventing unauthorized AI actions
Develop automated tests and 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
Select models and integration approaches with senior engineers
Implement logging, tracing, and monitoring for AI-powered services
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 on 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 while carefully reviewing generated code
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

Requirements

What you’ll need

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