Director Software Architect - Embedded AI

Honeywell•Atlanta, GA

15h•Hybrid

About The Position

As Director Software Architect – Embedded Artificial Intelligence (AI) at Honeywell Technologies, you will be the hands-on technical execution leader responsible for developing and deploying the embedded platform software portfolio, from operating systems to agentic frameworks. This influential leadership role supports AI-enabled technology solutions by delivering scalable embedded software capabilities, optimizing AI workloads for device-level execution, and advancing the broader platform roadmap through strong execution. The position is an individual-contributor role working within an extensive matrixed organization. You will collaborate across Honeywell Technologies Strategic Business Groups (SBGs) and with business leaders to align business and portfolio priorities. The work is deeply technical and execution-oriented, focused on building end-to-end platforms, optimizing and deploying software stacks, AI deployment frameworks, and embedded software. The role is based in Atlanta, Georgia, on a hybrid schedule and reports to the Senior Director Digital Services – Data & AI.

Requirements

At least 8 years of experience in software architecture, embedded software development, AI deployment, or related engineering roles.
Hands-on experience deploying software applications onto embedded devices or AI-enabled hardware platforms.
Demonstrated understanding of embedded software development, software stacks, AI deployment frameworks, and system-level AI execution on target hardware.
Must be a U.S. Person as defined for export-control compliance: a U.S. citizen, U.S. permanent resident, person with protected status under asylum or refugee status, or someone able to obtain export authorization.

Nice To Haves

Bachelor’s degree in a technical discipline such as science, technology, engineering, mathematics, computer science, or a related field.
Advanced degree in Computer Science, Engineering, Artificial Intelligence, Machine Learning, or a related field.
Background in system solutions with AI application deployment experience.
Working knowledge of AI acceleration technologies, GPUs, AI accelerators, model quantization, fine-tuning, and model optimization techniques.
Proven ability to create scalable embedded software solutions and deliver AI capabilities that operate effectively on real-world device platforms.
Experience building and managing pipelines for AI model deployment at the edge and optimizing AI workloads in embedded environments, including memory management, compute management, runtime optimization, and performance tuning.
Ability to work collaboratively in an agile, fast-paced, dynamic environment while maintaining technical rigor, execution focus, and a commitment to innovation and continuous learning.
Demonstrated technical leadership and problem-solving skills, including guiding execution, resolving complex engineering issues, and delivering working AI capabilities on devices.
Ability to partner with business teams and customers to understand requirements, gather feedback, and ensure solutions meet market and product needs.

Responsibilities

Lead technical implementation of platform deployment, optimization, and system-level AI execution on devices.
Architect and implement embedded software approaches that enable AI applications to run effectively within device memory, compute, power, and performance constraints.
Ensure cohesive integration across embedded software, firmware, hardware interfaces, testing processes, and AI software stacks.
Collaborate with cross-functional engineering, product, business, and customer-facing teams to translate requirements into executable technical plans and working device capabilities.
Drive technical execution from concept through deployment, aligning solutions with business objectives, product roadmaps, customer needs, scalability expectations, security, and compliance requirements.
Promote innovation, continuous improvement, and execution discipline across initiatives.
Mentor engineers through complex technical challenges.