Sr. Director of Cloud Engineering

Johnson Controls•Westford, MA

1d•$170,000 - $240,000•Remote

About The Position

The Sr. Director of Cloud Engineering leads cloud engineering and enterprise architecture across Johnson Controls’ Security organization. The role combines technical leadership with organizational management, overseeing engineering teams and delivery of cloud platforms, shared services, and AI-enabled capabilities that support multiple product lines, including Highspan and the evolution of the established product portfolio. The position defines cloud and AI technical strategy, establishes architecture standards, and turns business priorities into executable engineering plans. It partners with product-line engineering leaders and Product Management to align shared technology investments with roadmaps, manage dependencies, and deliver secure, scalable, and reliable solutions. This is a fully remote, U.S.-based position. The role owns strategy, architecture, delivery, quality, and operational outcomes for cloud and shared engineering capabilities. It leads globally distributed teams; manages staffing, capacity, budgets, and external resources; and develops engineering talent and leadership. It remains technically involved through architecture reviews, prototypes, and resolution of complex engineering problems. The position also leads architecture and integration for AI-enabled capabilities, establishing services, data flows, interfaces, and deployment patterns across cloud and edge environments. It sets approaches to evaluate and monitor AI capabilities and ensures privacy, access controls, model security, and appropriate human oversight. The role partners across Cybersecurity, DevOps, Program Management, Product Management, and product teams to establish secure engineering practices, operational readiness, reliability, recovery, and cost efficiency. The posted hiring salary range is $170,000–$240,000, with final salary depending on the applicant’s education, experience, knowledge, skills, abilities, internal equity, and market data. The role offers a competitive bonus plan based on individual, group, and corporate performance, as well as a competitive benefits package.

Requirements

Bachelor’s degree in Computer Science, Software Engineering, Computer Engineering, or a related technical discipline, or equivalent relevant experience.
12+ years of software engineering experience, including substantial experience designing and delivering cloud or distributed systems.
5+ years leading engineering teams.
Demonstrated experience leading engineering managers, architects, and globally distributed technical teams.
Proven accountability for delivery, quality, staffing, and engineering budgets for commercial software platforms or shared services.
Experience leading technical strategy and coordinating delivery across multiple product lines or business units.
Demonstrated experience architecting production SaaS platforms, including multi-tenancy, service integration, data management, and operational resilience.
Deep expertise in a major public cloud platform and ability to apply sound architecture principles across different technology environments.
Practical experience integrating AI or machine learning capabilities into production software, including deployment, evaluation, and monitoring.
Strong understanding of APIs, event-driven systems, containers, infrastructure automation, and CI/CD.
Experience designing secure systems, including identity, authorization, encryption, and customer data protection.
Ability to produce working prototypes, assess implementation details, and influence technical decisions across multiple teams.

Nice To Haves

Advanced degree (MS, MBA, or PhD) in a relevant technical or business discipline.
Experience with Microsoft Azure.
Background in physical security, video management, access control, IoT, or connected-device platforms.
Experience with video processing, streaming, storage, or edge AI deployment.
Experience with generative AI applications, retrieval-based systems, model-serving infrastructure, or AI lifecycle management.
Success modernizing established products and introducing shared capabilities across a product portfolio.
Experience collaborating with globally distributed engineering teams.
Relevant cloud architecture certification.

Responsibilities

Define and execute cloud engineering and enterprise architecture strategy across Security, aligning technology investments with business priorities and product roadmaps.
Set shared technical direction for cloud services, AI integration, data, APIs, identity, and connectivity across devices, on-premises systems, and cloud platforms.
Identify opportunities to consolidate overlapping capabilities, reduce duplication, and accelerate delivery through reusable platforms and services.
Partner with product-line leaders to establish ownership, prioritize shared engineering investments, and balance immediate delivery with long-term modernization.
Evaluate emerging technologies and guide investment decisions based on customer value, technical feasibility, cybersecurity, and total cost of ownership.
Lead globally distributed engineering teams responsible for cloud platforms and shared capabilities across product lines.
Establish responsibilities, decision authority, and collaboration practices across engineering managers, architects, and technical teams.
Recruit, develop, and retain engineering talent; strengthen leadership capability and succession readiness.
Manage staffing, capacity planning, engineering budgets, and external resources within the role’s scope.
Build a culture of customer focus, technical excellence, accountability, and continuous improvement.
Own delivery, quality, and technical outcomes for cloud and shared engineering capabilities.
Translate strategic priorities into plans with clear scope, milestones, resource commitments, and acceptance criteria.
Coordinate releases, manage dependencies, and resolve execution risks with Program Management and product-line engineering leaders.
Establish measures for delivery predictability, release quality, service reliability, engineering productivity, and operating cost.
Improve development, testing, deployment, and release practices through automation, CI/CD, and effective use of AI-assisted engineering tools.
Own architecture standards and governance across Security, providing practical direction for cloud, hybrid, and connected security solutions.
Guide design decisions involving scalability, availability, interoperability, tenant isolation, performance, and recovery.
Lead architecture reviews and ensure significant technical decisions document alternatives, trade-offs, and implementation guidance.
Maintain hands-on technical involvement through design reviews, targeted prototypes, and resolution of complex engineering issues.
Work with product-line teams to implement architecture improvements and verify shared capabilities meet product and customer requirements.
Lead architecture and engineering integration of AI-enabled capabilities across products and shared services in partnership with AI specialists and Product Management.
Establish services, data flows, interfaces, and deployment patterns for AI capabilities across cloud and edge environments.
Define evaluation and monitoring approaches for AI accuracy, latency, reliability, cost, and customer value.
Embed data privacy, access controls, model security, and appropriate human oversight into AI-enabled solutions.
Guide emerging AI technologies from focused experimentation into supported production capabilities.
Establish engineering practices that embed cybersecurity, observability, automated deployment, and recovery into cloud solutions.
Partner with Cybersecurity, DevOps, and product teams to address applicable security, privacy, and compliance requirements.
Ensure operational readiness of delivered services, including monitoring, support ownership, incident response, and disaster recovery planning.
Manage cloud and AI cost efficiency through architecture choices, capacity planning, and resource optimization.
Use production feedback and engineering metrics to improve reliability, performance, and cost to serve.