- Company Name
- Carda Health
- Job Title
- Full Stack AI Engineer
- Job Description
-
**Job title**: Full Stack AI Engineer
**Role Summary**: Design, develop, and deploy AI-driven features that enhance remote rehabilitation for patients. Own the end-to-end AI product lifecycle, from research and prototyping to production integration and monitoring.
**Expectations**:
- Serve as the first AI hire, setting technical standards for AI integration across the platform.
- Demonstrate end-to-end ownership of AI projects, ensuring reliable, safe, and high‑quality solutions.
- Collaborate cross‑functionally with clinicians, product managers, and engineers.
**Key Responsibilities**:
- Identify high‑impact AI use cases in collaboration with product and clinical teams.
- Rapidly prototype with tools such as OpenAI, Hugging Face, LangChain, Pinecone, and other rapid‑development platforms.
- Design, build, and maintain AI agent workflows, ensuring scalability, safety, and compliance.
- Integrate AI pipelines with backend APIs and infrastructure, providing robust observability.
- Conduct prompt engineering, evaluation, and optimization for LLMs and retrieval‑augmented generation.
- Shape internal AI stack, best practices, and ethical guidelines for scalable deployment.
**Required Skills**:
- 2+ years AI‑focused engineering experience; deep knowledge of LLMs, foundation models, prompt engineering, RAG, agents, and model evaluation.
- 5+ years full‑stack/backend software engineering, strong Python proficiency.
- Hands‑on experience with OpenAI, Gemini, Claude APIs and open‑source location models.
- Familiarity with audio–conversational AI and API integration (WebRTC/Websockets, LiveKit, Pipecat, Daily).
- Proven record of shipping end‑to‑end software in fast‑paced environments; ability to navigate ambiguity and rapid feedback.
- Passion for products that produce measurable real‑world impact.
**Required Education & Certifications**:
- Bachelor’s degree or higher in Computer Science, Engineering, Data Science, or a related field.
- Certifications in cloud platforms (AWS, GCP) or AI/ML are advantageous but not mandatory.
- Experience with HIPAA‑compliant healthcare data (FHIR, HL7, clinical notes) is a bonus.