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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in managing and developing engineering teams, particularly in the context of LLM-based systems and production environments. Strong focus on operational health, security compliance, and effective communication with diverse stakeholders.
Highest-signal resume keywords
LLM-Based Systems ManagementTeam Leadership and DevelopmentProduction Engineering FundamentalsSecurity and Compliance ExpertiseClear Communication Skills
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Software EngineeringAgent Runtime UnderstandingEvaluation and Retrieval SystemsIncident ManagementTesting and DeploymentPerformance ManagementMachine LearningModel Access and ObservabilityTechnical Trade-Off Decision MakingAI Workflow Prioritization
Soft Skills
Clear CommunicationCareer DevelopmentFeedback ProvisionCollaboration with StakeholdersAdaptability in Greenfield Spaces
Tools & Technologies
GCPAI Graded EvaluationsOn-Call SystemsIncident Response ToolsOperational Health Monitoring
Industry Keywords
HealthcareFinanceInsuranceHIPAA ComplianceSensitive Data Management
Tech Stack
Tools & technologiesGoogle Cloud Platform
About the role
Key responsibilities & impact- Hire, onboard, and develop Applied AI Engineers across Senior, Staff, and Senior Staff levels
- Grow the team from a single pod into multiple teams as work expands
- Drive the roadmap and execution of production LLM-based agents and assistants from scoping through launch and ongoing operation
- Partner with Staff+ engineers on architecture for agent runtime and orchestration, retrieval, model access, and observability
- Make technical trade-off decisions
- Establish evaluation sets, regression tests, and AI-graded evaluations as part of the shipping process
- Own operational health, including on-call, incident response, provider fallbacks, model upgrades, and AI spend
- Ensure AI systems protect patient data, follow least-privilege access, and defend against prompt injection
- Partner with Security and Compliance on HIPAA requirements
- Prioritize AI workflows and use cases with Product and Operations leaders
- Determine when agents should hand off to people and which initiatives to prioritize
- Explain AI capabilities, risks, and timelines to product, operations, clinical, and executive stakeholders
- Run planning, prioritization, and delivery rituals
- Provide direct feedback and build career paths
- Perform other duties as assigned
Requirements
What you’ll need- Bachelor's degree in Computer Science, Engineering, or a related technical field
- 10+ years of software engineering experience
- 3+ years managing engineers directly, including hiring, performance management, and career development
- Experience leading or building LLM-based systems in production used by real users
- Experience managing senior and Staff-level engineers and earning their technical trust
- Hands-on understanding of agent runtime, evaluation, retrieval, and observability
- Strong production engineering fundamentals across testing, services, APIs, deployment, incident management, and on-call
- Experience leading teams handling sensitive data with a security-first mindset
- Comfort building in a greenfield space
- Clear communication with technical and non-technical partners
- Preferred: healthcare, finance, or insurance experience
- Preferred: GCP experience
- Preferred: scaling engineering teams
- Preferred: model-version or provider migration experience
- Preferred: machine learning experience beyond LLMs
- Preferred: experience leading internal platforms used by engineering teams
Benefits
Comp & perks- Medical, Dental, and Vision plans
- Flexible Spending/Health Savings Accounts
- Flexible PTO
- 401(k) + Company Match
- Life Insurance
- Pet insurance
- Competitive base pay