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.
Lead Cloud AI Engineer
Zebra Zebra. Identify and evaluate emerging innovation opportunities across Platform Engineering and Cloud Infrastructure .
Tech Stack
Tools & technologiesAzureCloudDockerGoogle Cloud PlatformKubernetesPythonRPA
About the role
Key responsibilities & impact- Identify and evaluate emerging innovation opportunities across Platform Engineering and Cloud Infrastructure
- Conduct business and systems analyses and translate findings into user stories, system requirements, and solution concepts
- Coordinate and execute Proofs of Concepts (PoCs) and hands-on delivery activities
- Research, analyze, and report on Generative AI, Machine Learning, Robotic Process Automation, and Virtual Agents
- Act as the primary IT Cloud Innovation Liaison across innovation and product teams
- Plan, coordinate, and facilitate structured ideation workshops
- Promote modern engineering methodologies and cloud-native possibilities as an Innovation Evangelist
- Track, analyze, and report KPIs and business outcomes of innovation initiatives
- Establish and maintain an operating model for cloud-native AI/ML deployment across GCP and Azure
- Lead and mentor cloud and AI platform engineers
- Translate AI governance, cloud security guardrails, and regulatory requirements into technical specifications
- Integrate PII masking and RBAC into automated CI/CD pipelines
- Manage roadmap alignment within assigned technology portfolios
Requirements
What you’ll need- Bachelor's degree in Computer Science, Electronic Engineering, Computer Engineering, or related field
- 5+ years experience working on an operations style team (NOC, SOC, MOC, etc.) and troubleshooting networking, service desk, operations center and/or supporting cloud based Infrastructure
- Demonstrated experience with Google Gemini Enterprise and ability to build and deploy custom agents using the Agent Development Kit (ADK)
- Familiarity with Google Cloud Platform (GCP), Azure, OpenAI, and Anthropic
- Experience working in a global, heterogeneous, cloud and on-prem environment
- Knowledge of Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) architectures, and agentic AI patterns including Model Context Protocol (MCP), tool calling, and orchestration frameworks
- Experience deploying containerized AI solutions using Kubernetes (GKE/AKS), Docker, and robust CI/CD pipelines
- Understanding of enterprise cloud security, application/API security, and fine-grained identity systems
- Experience integrating PII masking and complex Role-Based Access Control (RBAC) frameworks
- Advanced scripting capabilities in Python or similar languages for automation, infrastructure provisioning (IaC), and automated testing
- Active professional-level cloud certifications are highly preferred, such as Google Cloud Professional Cloud Architect, Google Cloud Professional Machine Learning Engineer or AI Engineer
- Exposure to AI/ML systems, application security, or API security is a plus
- Travel up to 10%
Benefits
Comp & perks- Performance-based annual cash incentive at a target equal to 10% of base pay
- Healthcare
- Wellness benefits
- Inclusion networks
- Continued learning and development offerings
- Community service days
- Traditional insurances
- Parental leave
- Employee assistance program
- Paid time off
- Hybrid work
- Adaptable hours
- Summer Flex Fridays
- Focus Fridays
- Annual companywide well-being day
- Some roles may be eligible for long-term incentive equity awards