AI Platform & Enablement Engineer - Remote

Summary

Mutual of Omaha is seeking an AI Platform & Enablement Engineer to join their AI Operations team. The role involves partnering with application development teams to enable generative AI capabilities within enterprise applications while ensuring compliance and security.

Responsibilities

• Build and mature foundational patterns for enterprise use of AWS Bedrock within broader business applications
• Create and publish reference architectures, reusable integration patterns, and developer guidance for GenAI use cases
• Design and implement governance-as-code and compliance-as-code controls to support responsible AI adoption at scale
• Develop reusable guardrails, policy-aligned templates, and automation that help teams stay within approved enterprise standards
• Enable secure and scalable use of LLM agents, orchestration patterns, and supporting AWS services
• Partner with application developers to accelerate rapid proof-of-concept enablement and help teams move from experimentation to production-ready designs
• Translate governance, security, and architecture requirements into practical engineering controls that developers can adopt with minimal friction
• Track evolving AWS Bedrock capabilities and incorporate relevant enhancements into enterprise enablement patterns
• Design and implement cross-account AI usage data collection and aggregation infrastructure to support enterprise observability and executive reporting
• Automate evaluation and reporting for GenAI solutions, including quality, safety, and policy-alignment measures where appropriate
• Collaborate with Architecture, Security, Risk, Compliance, and platform teams to ensure GenAI solutions align to enterprise expectations without unnecessarily slowing innovation

Skills

• Hands-on experience as a software engineer or full stack engineer, with the ability to work credibly with application development teams
• Experience building and deploying cloud-native applications, APIs, and integrations in AWS
• Familiarity with AWS Bedrock and strong interest in generative AI application enablement
• Experience with infrastructure-as-code and automation using tools such as AWS CDK and CloudFormation
• Ability to translate technical, governance, and compliance requirements into practical implementation patterns and engineering controls
• Experience building reusable frameworks, templates, libraries, or platform capabilities that improve developer speed and consistency
• Comfort operating across a large, multi-account AWS environment — understanding how to design solutions that work at enterprise scale, not just in a single account
• Strong problem-solving and collaboration skills, with the ability to work across engineering, architecture, security, governance, and business teams
• Experience enabling or integrating generative AI capabilities into enterprise software applications
• Familiarity with LLM evaluation, testing, monitoring, or reporting frameworks
• Experience implementing platform controls such as guardrails, logging, auditability, or policy enforcement in cloud environments
• Experience publishing developer-facing technical standards, engineering patterns, or reference implementations
• Experience designing or operating cross-account AWS infrastructure — such as data aggregation pipelines, centralized logging, or multi-account governance tooling
• Exposure to regulated environments where engineering solutions must align to security, risk, and compliance expectations

Qualifications

Must Haves

• Hands-on experience as a software engineer or full stack engineer, with the ability to work credibly with application development teams
• Experience building and deploying cloud-native applications, APIs, and integrations in AWS
• Familiarity with AWS Bedrock and strong interest in generative AI application enablement
• Experience with infrastructure-as-code and automation using tools such as AWS CDK and CloudFormation
• Ability to translate technical, governance, and compliance requirements into practical implementation patterns and engineering controls
• Experience building reusable frameworks, templates, libraries, or platform capabilities that improve developer speed and consistency
• Comfort operating across a large, multi-account AWS environment — understanding how to design solutions that work at enterprise scale, not just in a single account
• Strong problem-solving and collaboration skills, with the ability to work across engineering, architecture, security, governance, and business teams

Nice to Haves

• Experience enabling or integrating generative AI capabilities into enterprise software applications
• Familiarity with LLM evaluation, testing, monitoring, or reporting frameworks
• Experience implementing platform controls such as guardrails, logging, auditability, or policy enforcement in cloud environments
• Experience publishing developer-facing technical standards, engineering patterns, or reference implementations
• Experience designing or operating cross-account AWS infrastructure — such as data aggregation pipelines, centralized logging, or multi-account governance tooling
• Exposure to regulated environments where engineering solutions must align to security, risk, and compliance expectations

Benefits

• Annual bonus opportunity
• 401(k) plan with a 2% company contribution and 6% company match
• Work-life balance with vacation, personal time and paid holidays