Sr. Solution Architect

Johnson Controls•Glendale, AZ

2d•Hybrid

About The Position

Johnson Controls International is seeking an AI Solution Architect to design and govern enterprise AI solutions across generative AI, agentic AI, machine learning, RAG, enterprise search and intelligent automation. You will work with AI engineers, platform engineers, software teams, data scientists, product teams, cyber security, enterprise architecture and business stakeholders to turn AI opportunities into secure, scalable and supportable solutions.

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.
AI Architecture: Generative AI, Agentic AI, RAG (Retrieval-Augmented Generation), enterprise search, document intelligence, evaluation, and AI safety.
Azure AI: Azure AI Foundry, Azure OpenAI, Azure AI Search, Azure Machine Learning, and approved model endpoints.
Integration: REST APIs, Azure API Management, event-driven architectures, messaging platforms, tool integration, and enterprise integration patterns.
Security: Microsoft Entra ID, managed identities, OAuth/OIDC, RBAC, private networking, secrets management, and secure-by-design principles.
Governance: Architectural decision records, Responsible AI, privacy, risk management, compliance, observability, and production readiness.
Leadership and ways of working: Strong systems thinking and judgement to balance innovation, speed, security, quality and maintainability.
Clear communication and ability to influence across 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 preferred.

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 clear architecture decisions.
Design 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 from the outset.
Define identity, RBAC, private networking, secrets, data protection, content safety and auditability patterns.
Document risks, assumptions, dependencies, mitigations and operational-readiness requirements.
Facilitate discovery and design workshops that turn ambiguous needs into phased delivery options.
Explain AI concepts, risks and trade-offs clearly to technical and non-technical stakeholders.
Provide technical leadership through reviews, mentoring and pragmatic architecture decisions.