Applied AI Engineer, Patient Experience

Job not on LinkedIn

🔥 28 minutes ago

🇺🇸 United States – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 AI Engineer

👻 Ghost score 25%

What it means: the chance that no one is really hiring for this job.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.Why this score:

• Just posted.
• Jobs at this company usually fill in 60 days.
• 102 open roles for a team of 16.
• No salary listed.

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Bask Health

WebsiteLinkedInAll Job Openings

11 - 50 employees

🏥 Healthcare

💼 Consulting

📦 Logistics

💰 Pre Seed Round on 2022-05

Healthcare • Consulting • Logistics

Bask Health is a robust platform providing a comprehensive suite of customizable telehealth solutions. It offers tools such as a questionnaire builder, patient portals, and pharmacy fulfillment services, all secured with strong encryption and HIPAA-compliance. Bask Health seamlessly integrates telehealth and e-commerce, enabling streamlined patient care from consultation to delivery. The platform supports entrepreneurs, doctors, and developers by offering scalable no-code solutions that enhance user experience and business growth. With its nationwide pharmacy network, Bask Health empowers businesses to efficiently manage prescriptions, patient data, and order fulfillment across the entire digital health landscape.

📋 Description

• 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

• 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

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