AI Architect
Job Description
AI Architect – Agentic AI Platform
Job Description:
We are seeking a highly skilled AI Architect on a contract basis to lead the design and implementation of a secure, enterprise grade Agentic AI Platform supporting Natural Language interaction, secure agent brokerage, and integration with numerous backend systems.This role will partner closely with our AI, Integration, and Automation leadership to architect a scalable platform in Azure or AWS, leveraging our existing Python-based FastAPI gateway, corporate automation toolchains, and hybrid cloud infrastructure.
The ideal candidate has deep experience with agentic AI systems, secure multi-agent architectures, Python, and cloud-native design patterns. You will design the platform's core components—including the Natural Language agent, broker/service mesh for agent communication, security model, agent execution runtime, and integration interfaces—while ensuring compliance with security and scalability expectations.
This is a hands-on architecture role requiring the ability to design system patterns, create reference implementations, and guide engineers across automation, infrastructure, and platform engineering teams.
Core Job Functions:
- Architect and design a secure, scalable Agentic AI platform running in Azure or AWS.
- Develop the platform's Natural Language agent layer, including orchestration patterns, context management, and retrieval/grounding strategy.
- Architect a secure agent broker capable of routing requests to numerous MCP (Model Context Protocol) servers with strict access control aligned to user entitlements.
- Design patterns for creating and deploying new automation-focused agents that can interact with infrastructure tools and business systems.
- Integrate the platform with:
o Existing Python FastAPI Entra-integrated API gateway (27 existing integrations)
o Jenkins orchestration jobs
o Ansible Automation Platform for configuration automation
o GitHub repositories, secrets, actions, and branching standards- Develop reference Python implementations for agents, security enforcement, and service interfaces.
- Partner with Infrastructure, Cloud, Identity, Security, and Automation teams to align design with enterprise standards.
- Define platform observability, including logging, monitoring, and agent execution traceability.
- Ensure platform meets corporate standards for identity, authentication, authorization, data governance, and secure cloud architecture.
- Establish best practices for agent lifecycle management, versioning, model evaluation, and deployment.
- Support knowledge transfer and documentation for internal development teams.
Experience:
- Proven experience architecting agentic AI systems, LLM backed automation, or multi-agent platforms.
- Hands-on cloud architecture experience with Azure and/or AWS in enterprise environments.
- Strong background in Python, particularly FastAPI, backend service design, and secure API development.
- Experience integrating AI systems with enterprise automation ecosystems (e.g., CI/CD tools, orchestration frameworks, configuration management systems).
- Practical experience applying security-by-design principles within highly regulated or Fortune 500+ environments.
- Demonstrated ability to design for high availability, scalability, and operational reliability.
- Experience working in hybrid infrastructure environments integrating on prem systems with cloud services.
Required Qualifications:
- 7+ years designing distributed systems or AI driven applications.
- 4+ years hands-on cloud architecture experience (Azure, AWS, or both).
- Strong Python development skills, with experience building production-grade services.
- Experience building or integrating with:
o LLM frameworks (OpenAI, Azure OpenAI, Anthropic, etc.)
o Agent frameworks or orchestration layers (LangChain, Semantic Kernel, Haystack, etc.)
o Secure API ecosystems- Deep understanding of authentication/authorization models, including OAuth2, Entra ID, service principals, scopes, and RBAC.
- Experience designing secure communication between distributed services (service mesh, queues, event buses, or structured RPC patterns).
- Ability to translate business workflows into automated or AI-driven processes.
- Excellent written and verbal communication skills.
Preferred Qualifications:
- Experience with Model Context Protocol (MCP) server design or integration.
- Knowledge of MLOps, LLM evaluation frameworks, vector databases, and prompt engineering.
- Prior experience building agent brokers, model routers, or structured tool execution systems.
- Experience with infrastructure automation tools such as:
o Jenkins (pipelines, shared libraries)
o Ansible Automation Platform- Familiarity with GitHub Enterprise, GitHub Actions, and enterprise branching standards.
- Experience working with Fortune 100 or global enterprises with stringent security and compliance requirements.
- Background in infrastructure operations, platform engineering, or cloud automation.