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Bask Health

Senior Applied AI Engineer – Patient Experience

Bask Health

. Design, develop, and deploy AI-powered features across Bask Health's patient-facing applications.

Posted 11/12/2026full-timeRemote • United StatesSeniorWebsite

Core Competencies

Role fit
Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in developing AI-powered applications, particularly with large language models, while ensuring compliance with data privacy and security standards. Capable of collaborating across teams to design and implement user-centered AI features that enhance patient interactions.

Highest-signal resume keywords
AI-Powered Application DevelopmentLarge Language Model IntegrationPython ProgrammingAPI Design and Service IntegrationData Privacy and Security Compliance

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills
PythonTypeScriptJavaScriptPrompt EngineeringModel EvaluationWorkflow OrchestrationRetrieval-Augmented GenerationDatabase ManagementApplication SecurityAI Application Testing
Soft Skills
Strong Communication SkillsAnalytical ThinkingProblem-Solving SkillsCollaborationMentoring
Tools & Technologies
OpenAILangChainAWSPostgreSQLNode.jsReactNext.jsPineconeWeaviateClaude Code
Industry Keywords
HealthcareTelehealthDigital HealthHIPAA CompliancePatient Onboarding

Tech Stack

Tools & technologies
AWSCloudJavaScriptNext.jsNode.jsPostgresPythonReactTypeScript

About the role

Key responsibilities & impact
  • Design, develop, and deploy AI-powered features across Bask Health's patient-facing applications.
  • Build intelligent experiences for onboarding, questionnaires, and digital care workflows.
  • Develop AI-assisted interfaces that simplify complex patient interactions.
  • Integrate large language models into frontend and backend applications.
  • Build production services supporting patient-facing AI features.
  • Design retrieval-augmented generation systems using approved knowledge sources.
  • Implement structured outputs, tool calling, and workflow orchestration.
  • Develop AI-assisted patient support and information experiences within approved boundaries.
  • Collaborate with clinical and product stakeholders to define safe AI behavior and escalation requirements.
  • Create safeguards, uncertainty handling, human review, and escalation mechanisms.
  • Design evaluation datasets and testing procedures.
  • Measure response accuracy, relevance, latency, reliability, and user experience.
  • Implement monitoring and observability for production AI applications.
  • Investigate model failures, unexpected outputs, and performance issues.
  • Optimize prompts, retrieval pipelines, and application logic.
  • Evaluate AI models and providers based on performance, cost, reliability, and operational requirements.
  • Develop secure integrations between AI services and Bask platform APIs.
  • Ensure authentication, authorization, data access controls, and privacy-conscious handling of patient information.
  • Collaborate with frontend engineers on responsive AI-powered interfaces.
  • Build reusable components and backend services.
  • Write maintainable, well-tested code and participate in technical design reviews.
  • Contribute to architecture discussions and establish applied AI engineering standards.
  • Mentor engineers and share production AI knowledge.
  • Use experimentation and product feedback to improve patient workflows.
  • Own features from technical design through deployment, monitoring, and iteration.

Requirements

What you’ll need
  • 5+ years of professional software engineering experience, including substantial experience building AI-powered applications.
  • Demonstrated experience shipping LLM-powered or machine learning features into production.
  • Strong programming skills in Python, TypeScript, JavaScript, or comparable languages.
  • Experience integrating large language models through production APIs.
  • Strong understanding of modern LLM application architecture.
  • Hands-on experience with prompt engineering, structured outputs, and model integration patterns.
  • Experience building retrieval-augmented generation systems or similar knowledge-grounded AI applications.
  • Familiarity with embeddings, semantic retrieval, and search infrastructure.
  • Experience implementing tool calling, workflow orchestration, or multi-step AI processes.
  • Strong backend engineering skills, including API design and service integrations.
  • Experience working with databases, application state, and production data systems.
  • Understanding of model evaluation and AI application testing methodologies.
  • Experience measuring and improving AI response quality, latency, and reliability.
  • Familiarity with production monitoring, logging, and troubleshooting.
  • Experience implementing fallback behavior and error handling for AI-dependent applications.
  • Understanding of application security, authentication, authorization, and data privacy.
  • Ability to design safeguards for sensitive or high-impact AI workflows.
  • Experience collaborating with frontend engineers to deliver end-user product features.
  • Strong understanding of software testing, code review, and deployment practices.
  • Familiarity with cloud infrastructure and production application environments.
  • Ability to translate product requirements into maintainable technical solutions.
  • Strong communication skills and experience working across engineering and product teams.
  • Ability to independently own complex technical projects from design through production.
  • Strong analytical thinking and practical problem-solving skills.
  • Interest in building reliable, user-centered AI products.
  • Nice to Have: Experience developing AI-powered applications in healthcare, telehealth, or digital health.
  • Nice to Have: Familiarity with HIPAA and healthcare data privacy considerations.
  • Nice to Have: Experience building patient-facing chat interfaces, assistants, or guided workflows.
  • Nice to Have: Experience designing AI systems with clinical oversight or human-in-the-loop review.
  • Nice to Have: Familiarity with healthcare workflows, patient onboarding, and treatment-related communication.
  • Nice to Have: Experience with OpenAI, Anthropic, or comparable model providers.
  • Nice to Have: Experience using LangChain, LangGraph, or similar orchestration frameworks.
  • Nice to Have: Familiarity with vector databases such as Pinecone, Weaviate, or pgvector.
  • Nice to Have: Experience developing conversational AI systems.
  • Nice to Have: Experience with agentic AI workflows and tool-using assistants.
  • Nice to Have: Familiarity with model evaluation frameworks and automated LLM testing.
  • Nice to Have: Experience with prompt versioning and experiment tracking.
  • Nice to Have: Experience using React, Next.js, or modern frontend frameworks.
  • Nice to Have: Experience building backend services with Node.js and TypeScript.
  • Nice to Have: Familiarity with PostgreSQL, Prisma, Drizzle, or similar data tools.
  • Nice to Have: Experience deploying applications on AWS or comparable cloud platforms.
  • Nice to Have: Familiarity with serverless architectures and event-driven systems.
  • Nice to Have: Experience optimizing LLM inference costs and application latency.
  • Nice to Have: Experience with AI-powered search, knowledge retrieval, or personalization.
  • Nice to Have: Experience using AI-assisted development tools such as Cursor or Claude Code.