Senior Staff Applied AI Engineer – Tech Lead

This is a fully remote position, open to applicants in United States, +1 more country.

📋 Description

• Establish the technical roadmap for agent runtime and orchestration.

• Develop evaluation frameworks, including regression tests and AI-based assessments.

• Specify model access and operations, covering provider routing, version upgrades, and outage strategies.

• Take ownership of observability and cost attribution for AI systems.

• Create retrieval and grounding mechanisms over company data.

• Convert human workflows into agent workflows and identify tasks that must remain human-led.

• Safeguard patient information while ensuring security and privacy in AI systems.

• Make decisions regarding cloud and data infrastructure on GCP, collaborating with the Data Platform team.

• Perform code and design reviews and mentor engineers who are new to AI.

• Articulate AI trade-offs to product, operations, and clinical stakeholders.

• Oversee AI architecture and technical quality, partnering with the AI Engineering Manager on personnel and delivery.

• Maintain long-term technical direction for AI across the organization until an AI Principal Engineer is appointed.

⛳️ Requirements

• A minimum of 12 years of software engineering experience, including proven technical leadership (tech lead, staff, or principal-level scope).

• At least two years of experience in building and operating LLM-based systems in production, not limited to demos or personal projects.

• In-depth, hands-on knowledge of agent runtime or evaluation, along with familiarity across the broader AI engineering stack.

• A history of assessing AI quality using legitimate evaluation methods and data.

• Experience guiding a small team's technical direction from the ground up, or nearly so.

• Preferred experience in healthcare or another regulated industry (PHI, HIPAA).

• Familiarity with GCP is preferred.

• Experience in developing an internal platform utilized by other engineering teams is preferred.

• Background in both classic machine learning and LLMs is preferred.

• Experience scaling a team from a single unit to multiple teams is preferred.

• Authorization to work in the job posting location is required.

🏝️ Benefits

• Medical, Dental & Vision coverage.

• Flexible Spending / Health Savings Accounts.

• Generous Paid Time Off (PTO).

• Hybrid work flexibility.

• 401(k) with Company Match.

• Life Insurance.

• Pet Insurance.

• Competitive salary package.