AI/ML Platform & Agentic Automation Engineer

Peraton is hiring an AI/ML Platform & Agentic Automation Engineer to integrate approved AI models and managed services into enterprise platforms through reusable APIs and agentic workflows. The role also develops developer-assistance and self-service automation while supporting secure, auditable operations across cloud and restricted environments.

Responsibilities

• Integrate approved foundation models and managed AI services, including AWS Bedrock or comparable platforms, into enterprise applications and workflows
• Develop reusable APIs, service wrappers, and integration patterns that enable consistent access to model capabilities
• Implement configurable model-selection and integration approaches that support model updates without requiring extensive changes to consuming applications
• Support deployment and integration within cloud and restricted environments where approved AI services are available
• Design and implement agentic workflows to automate repeatable platform engineering, service management, and operational processes
• Integrate AI agents with approved tools and APIs, including IT service management platforms, source control systems, infrastructure automation, knowledge repositories, and observability services
• Establish appropriate workflow boundaries, approval requirements, tool permissions, auditability, and failure-handling mechanisms
• Develop reusable automation components for account provisioning, access requests, environment deployment, incident enrichment, technical documentation retrieval, and other approved use cases
• Develop and maintain AI-powered developer assistants, chat interfaces, and low-code/no-code capabilities
• Connect developer-facing tools to approved technical documentation, platform guidance, service catalogs, code examples, and engineering resources
• Integrate AI assistance into development workflows while protecting credentials, sensitive information, and privileged platform functions
• Collaborate with platform and developer-support teams to identify repetitive requests that can be addressed through self-service tools and guided automation
• Integrate AI services with identity and access management, role- and attribute-based access controls, service identities, secrets management, and audit mechanisms
• Enforce established security boundaries, access policies, and tenant isolation requirements across AI services and agent workflows
• Coordinate with cybersecurity teams to implement appropriate guardrails, data-handling controls, logging, and authorization requirements
• Instrument AI services and automated workflows to support monitoring of availability, usage, failures, latency, and performance
• Maintain AI platform components, workflow definitions, prompts, tool integrations, and configuration through source control and established engineering review processes
• Develop automated tests and evaluation scenarios to validate critical workflows before deployment to operational environments
• Troubleshoot model-service integrations, agent behavior, workflow failures, and developer-assistance capabilities
• Evaluate approved model and service updates and coordinate controlled implementation with AI/ML operations, assurance, and platform engineering teams