Senior Software Engineer, AI

Remote

Pear VC

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About UpDoc

At UpDoc, we are building the world's first clinically validated, physician-supervised conversational agent that manages chronic diseases; the first step towards a true "AI doctor". With partners including Stanford, Mayo Clinic, Eli Lilly, UCSF Health, and Microsoft, UpDoc is working to build a future where all patients can access high-quality, high-touch care. Learn more about us here.

We are seeking a talented and motivated senior engineer to join our team. You will primarily work on UpDoc’s patient-facing conversational agent. This is a fully remote position.

Who You Are

You’re an experienced senior engineer with a backend tilt. You’re well-versed in all things web and have experience building LLM applications end-to-end, even if not in a professional context. You follow the AI/LLM space closely, play with new technologies as they come out, and are excited to use these technologies to build safe, reliable medical AI systems.

What You'll Do

  • Lead the development of our patient-facing conversational agent

  • Implement a scalable, low-latency system for voice/multimodal conversations

  • Implement rigorous prompt engineering processes and develop useful metrics for system evaluation

  • Identify where fine-tuning and alignment might be valuable, and create data pipelines to enable fast experimentation

  • Work with other backend engineers to deploy AI models and chat/voice APIs

  • Help identify, evaluate, and implement emerging LLM technologies, tools and frameworks

  • Collaborate with clinical experts to validate performance and medical accuracy

  • Work on developing backend services using FastAPI and Pydantic

What You’ll Need

  • 5+ years of professional software development experience, including 2+ years of experience with backend web development

  • Experienced and comfortable working with type-hinted, modern Python

  • 2+ years of experience building end-to-end LLM applications, personally or professionally

    • Experience integrating/optimizing LLMs in production environments

    • Knowledge of evaluation frameworks

    • Knowledge and experience with MLOps/LLMOps best practices

    • Experience building AI infrastructure from 0 -> 1

  • Experience with cloud platforms (especially Azure) and containerization technologies

Highly Desired

  • Professional experience building end-to-end LLM-powered applications

  • Experience with model fine-tuning/alignment

  • Experience in an early stage startup environment

  • Experience with healthcare industry standards, such as FHIR, and regulations, including HIPAA and SOC 2

Why You Should Join Us

  • Join a small, high-impact team building the future of healthcare

  • Work with cutting-edge LLM tools that support world-class medical institutions

  • Shape core technical architecture in an emerging field

  • Competitive compensation and equity in an early-stage startup

Interview Process

  1. Application form

  2. Conversation with our CTO

  3. Technical interviews:

    1. Coding interview focused on a real-world application relevant to the role (e.g., LLMs, backend engineering)

    2. Architecture/whiteboarding interview focused on discussing general application-design relevant to the role

  4. Conversation with our CEO

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Tags: APIs Architecture Azure Data pipelines Engineering FastAPI LLMOps LLMs ML infrastructure MLOps Pipelines Prompt engineering Python

Perks/benefits: Competitive pay Equity / stock options Startup environment

Region: Remote/Anywhere

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