The company is looking to develop and manage cutting-edge AI infrastructure for its complex enterprise environment, enabling the management of autonomous agents, machine learning systems, and other AI applications.
Requirements
- Experience with AI/ML infrastructure, agent orchestration, or similar AI-powered development tools.
- Proficiency in Python, TypeScript/JavaScript, and experience with AI/ML frameworks and libraries.
- Strong understanding of enterprise software architecture patterns and distributed systems design.
- Experience with cloud platforms (AWS, Azure, or GCP) and infrastructure-as-code tools.
- Experience with Docker, Kubernetes, and container orchestration in production environments.
- Experience building and managing APIs, microservices, and event-driven architectures.
- Strong understanding of information security principles, OAuth 2.0/OpenID Connect flows, API security, and secure system design.
Responsibilities
- Design and implement AI infrastructure to support federated agent development and distributed deployment across the organization.
- Manage and orchestrate AI agents to generate architecturally sound code, ensuring adherence to enterprise standards and best practices.
- Build and maintain MCP (Model Context Protocol) servers and related infrastructure for agent communication, coordination, and enterprise service bus integration.
- Accelerate code review processes by leveraging AI agents for automated analysis, quality checks, and architectural validation.
- Establish robust monitoring, governance, and security frameworks for AI agent operations in enterprise environments.
- Implement and manage secure authentication and authorization systems for MCP servers, including OAuth flows and API security.
- Collaborate with development teams to integrate AI-powered tools into existing workflows and CI/CD pipelines.
Other
- Act as a deployed engineer, traveling to different teams across the firm to teach AI infrastructure best practices and guide adoption.
- Provide technical leadership in transitioning traditional development practices to AI-augmented approaches.
- Strong communication and teaching skills with the ability to work as a deployed engineer across different teams.
