Sr. Solution Architect

Johnson Controls•Glendale, AZ

2d•$140,000 - $160,000•Hybrid

About The Position

Johnson Controls is seeking an AI Solution Architect to design and govern enterprise AI solutions across generative AI, agentic AI, machine learning, retrieval-augmented generation (RAG), enterprise search, and intelligent automation. The architect will work with AI and platform engineers, software teams, data scientists, product teams, cybersecurity, enterprise architecture, and business stakeholders to turn AI opportunities into secure, scalable, and supportable solutions. The role leads solution architecture for enterprise AI initiatives, translating business needs into end-to-end architectures, roadmaps, and non-functional requirements. It defines reusable reference architectures and integration patterns, and designs solutions using Azure AI services and approved enterprise APIs. The architect establishes patterns for RAG, conversational AI, document intelligence, multimodal workflows, and AI agents, along with approaches for model selection, evaluation, safety, grounding, cost, and operational reliability. The position aligns solutions with approved platforms, deployment patterns, networking, and operational controls; partners with engineering teams on APIs, data flows, application boundaries, reviews, and production readiness; and ensures AI traffic follows enterprise API management patterns. It embeds security, privacy, accessibility, compliance, and Responsible AI requirements, and defines identity, access, networking, data protection, content safety, and auditability patterns. The architect also facilitates discovery and design workshops, communicates AI concepts and trade-offs to varied audiences, and provides technical leadership through reviews, mentoring, and architecture decisions.

Requirements

Bachelor's degree in a relevant discipline, or equivalent practical experience.
8+ years in solution architecture, software engineering, cloud architecture, or enterprise technology roles.
Proven experience designing and delivering production Azure solutions in complex enterprise environments.
Hands-on architecture experience with generative AI, LLMs, RAG, conversational AI, document intelligence, or agent-based solutions.
Ability to guide solutions from discovery through design, delivery, governance approval, and operational support.
Knowledge of generative AI, agentic AI, RAG, enterprise search, document intelligence, evaluation, and AI safety.
Expertise with Azure AI Foundry, Azure OpenAI, Azure AI Search, Azure Machine Learning, and approved model endpoints.
Knowledge of REST APIs, Azure API Management, event-driven architectures, messaging platforms, tool integration, and enterprise integration patterns.
Knowledge of Microsoft Entra ID, managed identities, OAuth/OIDC, RBAC, private networking, secrets management, and secure-by-design principles.
Knowledge of architectural decision records, Responsible AI, privacy, risk management, compliance, observability, and production readiness.
Strong systems thinking and judgment to balance innovation, speed, security, quality, and maintainability.
Clear communication skills and ability to influence technical, product, and business teams.
Comfort facilitating workshops, resolving ambiguity, and presenting options with trade-offs.

Nice To Haves

Experience with Microsoft Agent Framework, Semantic Kernel, LangGraph, LangChain, or similar orchestration frameworks.
Experience with vector-capable data services such as Cosmos DB, Redis, PostgreSQL/pgvector, or similar.
Familiarity with Terraform, Kubernetes, Azure Container Apps, AKS, Azure API Management, and landing-zone patterns.
Azure Solutions Architect Expert, Azure AI Engineer Associate, TOGAF, or comparable certification.

Responsibilities

Lead architecture and solution design for enterprise AI initiatives across business domains.
Translate business needs into end-to-end solution architectures, roadmaps, and non-functional requirements.
Define reusable reference architectures, integration patterns, and architecture decisions.
Design AI solutions using Azure AI Foundry, Azure OpenAI, Azure AI Search, Azure Machine Learning, vector stores, and approved enterprise APIs.
Define patterns for RAG, conversational AI, document intelligence, multimodal workflows, and AI agents.
Establish approaches for model selection, evaluation, safety, grounding, cost, and operational reliability.
Align solutions with approved platform capabilities, deployment patterns, networking, and operational controls.
Ensure AI traffic follows enterprise API management patterns for authentication, observability, throttling, and cost allocation.
Partner with engineering teams on APIs, data flows, application boundaries, reviews, and production readiness.
Embed security, privacy, accessibility, compliance, and Responsible AI requirements in solution designs.
Define patterns for identity, RBAC, private networking, secrets, data protection, content safety, and auditability.
Document risks, assumptions, dependencies, mitigations, and operational-readiness requirements.
Facilitate discovery and design workshops and translate ambiguous needs into phased delivery options.
Explain AI concepts, risks, and trade-offs to technical and non-technical stakeholders.
Provide technical leadership through reviews, mentoring, and pragmatic architecture decisions.