FREE ACCESS
5,000–10,000 jobs/day
See all jobs on Scoutfield
Search thousands of fresh jobs every day.
Discover
- Fresh listings
- Fast filters
- No subscription required
Create a free account and start exploring right away.
Principal – AI Engineering
Interview Kickstart. Architect and implement automated CI/CD governance pipelines .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in architecting and implementing automated CI/CD governance pipelines, embedding Security and Responsible AI (RAI) into workflows, and developing real-time observability for production LLMs. Proficient in building AI integrations and designing secure Identity and Access Management (IAM) mechanisms.
Highest-signal resume keywords
CI/CD AutomationAI IntegrationsReal-Time ObservabilityIdentity And Access Management (IAM)Security And Responsible AI (RAI)
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Platform EngineeringApplied Machine Learning EngineeringAI ScienceAI Agent SimulationBenchmarking SolutionsAPI DevelopmentEnterprise-Scale AI InfrastructureGovernance PipelinesRouting MechanismsAutonomous AI Workflows
Industry Keywords
Compliance GuardrailsDeployment WorkflowsProduction LLMsTechnical OwnershipEnterprise Governance Systems
About the role
Key responsibilities & impact- Architect and implement automated CI/CD governance pipelines
- Embed Security, Responsible AI (RAI), and compliance guardrails into deployment workflows
- Build AI agent simulation, evaluation, and benchmarking solutions
- Develop real-time observability for production LLMs
- Develop APIs and integrations connecting AI development platforms with enterprise governance systems
- Design IAM and routing mechanisms for secure execution of autonomous AI workflows
- Take hands-on technical ownership of AI integrations, CI/CD automation, agent evaluation, and real-time observability
Requirements
What you’ll need- At least 6 years of experience in platform engineering, applied machine learning engineering, or AI science
- Experience architecting and building enterprise-scale AI infrastructure
- Experience with AI integrations
- Experience with CI/CD automation and governance pipelines
- Experience with AI agent simulation, evaluation, and benchmarking
- Experience with real-time observability for production LLMs
- Experience developing APIs and integrations connecting AI development platforms with enterprise governance systems
- Experience designing Identity and Access Management (IAM) and routing mechanisms
- Ability to embed Security, Responsible AI (RAI), and compliance guardrails into deployment workflows
- Ability to ensure autonomous AI workflows operate securely, reliably, and at scale
- Must work in the United States
Benefits
Comp & perks- Hybrid work arrangement
- Full-time employment on the client's payroll