Platform Engineer

Platform Engineer - AI & DevOps (Hybrid | Charlotte, NC or Detroit, MI)

Role Overview

Optomi, in partnership with a leading financial client, is seeking an AI Platform Engineer to build and scale the platform, tooling, and automation that powers our growing AI agent ecosystem. This role sits at the intersection of Platform Engineering, DevOps, and AI, focusing on the frameworks, integrations, CI/CD pipelines, and developer tooling that enable AI-powered solutions to operate reliably at enterprise scale.

This position is responsible for building the foundation that other developers rely on. Rather than developing AI models or agents directly, the focus is on building shared libraries, APIs, deployment patterns, automation frameworks, and platform capabilities that allow AI solutions to be deployed, governed, and scaled across the organization.

The ideal candidate brings strong Python development experience, a background in platform engineering or developer tooling, and experience building enterprise-grade CI/CD pipelines, API integrations, and automation solutions within AWS environments.

Key Responsibilities:

• Design, develop, and maintain the shared platform, tooling, and automation framework that supports AI agents and AI-driven development initiatives.
• Partner closely with Enterprise DevOps teams to ensure AI automation solutions align with enterprise architecture, security, and deployment standards.
• Build and maintain reusable Python libraries, frameworks, SDKs, and integration modules that support agent development and execution.
• Develop and manage CI/CD pipeline integrations, automated validation gates, and deployment workflows for AI workloads using GitLab CI/CD, GitHub Actions, Jenkins, or similar technologies.
• Build security-focused automation and remediation capabilities that identify vulnerabilities and enforce quality controls throughout the software delivery lifecycle.
• Create pipeline stages and automated controls that support coverage validation, vulnerability scanning, SRE readiness assessments, and deployment approvals.
• Develop reusable REST API integrations and shared service modules for systems such as Jira, Confluence, Dynatrace, and other enterprise platforms.
• Establish standards for Python packaging, dependency management, version control, and distribution across developer and CI/CD environments using tools such as Poetry and pip.
• Design and maintain JSON schemas, data contracts, configuration standards, and file management patterns that support interoperability across automation components.
• Improve developer productivity by creating templates, onboarding assets, initialization scripts, documentation, and reusable tooling that accelerates adoption of the platform.
• Support the onboarding of new AI agents and automation capabilities by building scalable deployment patterns, runtime management frameworks, and integration standards.
• Continuously identify opportunities to reduce manual effort, eliminate duplicate implementations, and improve platform consistency across teams.
• Collaborate with engineering teams to ensure AI agents, automation frameworks, and platform services meet enterprise-grade reliability, scalability, and security standards.

Required Qualifications:

• 4+ years of experience in Platform Engineering, DevOps Engineering, Software Engineering, Developer Tools, Infrastructure Engineering, or related technical disciplines.
• Strong Python development experience with a focus on building reusable libraries, frameworks, automation solutions, SDKs, or internal developer tooling.
• Experience designing, building, and supporting CI/CD pipelines and deployment automation.
• Experience with GitLab CI/CD (preferred), GitHub Actions, Jenkins, or similar pipeline technologies.
• Strong understanding of REST APIs, authentication methods, error handling, retries, pagination, versioning, and integration best practices.
• Experience developing shared tooling, internal platforms, SDKs, frameworks, or developer-facing services used by multiple teams.
• Experience working with JSON, JSON Schema, structured data formats, configuration management, and API-driven integrations.
• Experience supporting AWS-based environments and cloud-native development practices.
• Strong problem-solving skills and the ability to collaborate effectively with software engineering, DevOps, and platform teams.

Preferred Qualifications:

• Experience supporting AI, Generative AI, LLM-based applications, AI agents, autonomous workflow automation, or AI platform initiatives.
• Familiarity with Anthropic Claude, Claude Code, MCP (Model Context Protocol), OpenAI, LangChain, or similar AI technologies.
• Experience implementing security automation, vulnerability remediation workflows, and DevSecOps practices within CI/CD pipelines.
• Experience integrating with Jira, Confluence, Dynatrace, or other enterprise platforms through REST APIs.