Staff Applied AI Engineer — End-to-End Healthcare AI Deployments

Concurrence; San Francisco (CA); On-site; USD 240,000 - 300,000; Full time

Benefits offered by this job

Health insurance

Lunch provided

Mental health support

Wellness stipend

Learning budget

Conference attendance budget

Team offsite

Unlimited PTO

Job summary

Concurrence is hiring a Staff Applied AI Engineer to own the most complex customer use cases and steer technical direction across deployments. You’ll take deployments from brief to production, making architecture calls and staying hands-on in the toughest parts of the build.

Success is measured by real impact: more intake, fewer denials, faster billing closes. You’ll design scalable agent systems, handle diverse data, and craft platform capabilities from field-proven patterns.

Qualifications

• Shipped and owned complex production systems with real users depending on them.
• Led technical decisions across multiple projects or teams.
• Experience building with LLMs and agents in production, or depth to get there fast.
• Ability to handle non-deterministic systems with rigor.

Responsibilities

• Own complex use cases end-to-end from brief to production.
• Build agent systems with hierarchical structures and safety gates.
• Integrate with EHRs and legacy systems across various data shapes.
• Translate field patterns into platform capabilities and shared data lookups.
• Raise scope or integration concerns early to protect timelines.
• Mentor engineers and contribute to architecture and standards.

Skills

Production systems

Technical leadership

LLMs & agents

Customer-facing

Job description

Concurrence is hiring a Staff Applied AI Engineer to own the most complex customer use cases and steer technical direction across deployments. You’ll take deployments from brief to production, making architecture calls and staying hands-on in the toughest parts of the build.

Success is measured by real impact: more intake, fewer denials, faster billing closes. You’ll design scalable agent systems, handle diverse data, and craft platform capabilities from field-proven patterns.