Senior AI Engineer: Patient-Centric Conversational Agents

Clera; San Francisco (CA); On-site; USD 150,000 - 220,000; Full time

Job summary

Clera in San Francisco, CA is seeking an engineer to own patient-facing AI conversation loops end-to-end, building robust agent systems that improve patient outcomes. You will implement tool integrations, evals, and retrieval systems, and automate clinic workflows through code.

The role requires hands-on experience with LLM/agent systems, strong CS and math fundamentals, and an autonomous mindset to make architectural decisions in a fast-paced environment.

Qualifications

• Experience building and shipping LLM or agent systems end to end across professional roles, personal projects, research, or open source.
• Hands on experience with agent infrastructure: evals, retrieval, and tool integrations.
• Strong CS and math fundamentals; elite academic signals are a plus.
• Automation mindset with a track record of removing recurring manual workflows via code.
• Warmth and empathy for patient facing interactions and ability to extract product learnings from conversations.
• Autonomy to own systems in a fast moving environment with minimal supervision.
• Existing US work authorization; visa sponsorship not available.
• Proficiency in Python or equivalent for building agent infrastructure.

Responsibilities

• Diagnose why AI conversations with patients fail and ship fixes to prevent recurrence.
• Build and maintain agent infrastructure including tool integrations, evals, and retrieval systems.
• Automate recurring manual workflows on the clinic side to reduce toil through code.
• Handle patient facing interactions with warmth when the AI falls short and translate these moments into product insights.
• Own systems end to end with minimal oversight and make architectural decisions independently.

Skills

Python

Agent infrastructure

End-to-end systems

CS fundamentals

Mathematics

Job description

Clera in San Francisco, CA is seeking an engineer to own patient-facing AI conversation loops end-to-end, building robust agent systems that improve patient outcomes. You will implement tool integrations, evals, and retrieval systems, and automate clinic workflows through code.

The role requires hands-on experience with LLM/agent systems, strong CS and math fundamentals, and an autonomous mindset to make architectural decisions in a fast-paced environment.