Advanced AI Software Engineer

Honeywell

Phoenix, AZ

Hybrid

Who this role is best for

Best suited to candidates with advanced AI/ML engineering experience working in enterprise software environments.

Best fit for

Candidates with 4+ years of AI/ML engineering experience and a track record of deploying enterprise-grade AI solutions
— “4+ years of hands-on AI/ML engineering experience, including designing, developing, deploying, and supporting AI/ML and Generative AI solutions in production environments.”
Individuals with deep expertise in generative AI, LLMs, and agentic AI systems
— “deep expertise in Large Language Models (LLMs), Generative AI, agentic AI, machine learning, and software engineering to build secure, scalable, reliable, and production-ready AI solutions.”
Candidates who have experience with cloud-native AI solutions and integration with enterprise systems
— “Design and implement cloud-native AI solutions and integrate AI services with existing enterprise applications, APIs, data platforms, and software architectures.”

Things to consider

First 90 days require full-time onsite presence in Phoenix, Arizona
— “For the first 90 days, new hires must be prepared to work onsite 100% M-F.”
The role involves cross-functional collaboration with product, data, and cybersecurity teams
— “Collaborate closely with software, product, data, cloud/platform, cybersecurity, and architecture teams to translate complex business requirements into robust AI-powered solutions.”

How to stand out

Highlight experience with prompt engineering and semantic search in your resume and interviews
— “Design and implement advanced architectures, prompt and context-management strategies, embeddings, vector databases, semantic/hybrid search, reranking, and knowledge-retrieval pipelines.”
Demonstrate your ability to optimize AI workloads for performance and cost efficiency
— “Optimize AI workloads for latency, throughput, scalability, token consumption, infrastructure utilization, and cost.”
Showcase your experience with cloud-based AI infrastructure such as Azure AI or Vertex AI
— “Experience with Azure AI services/Azure AI Foundry and/or Google Gemini/Vertex AI and cloud-based AI infrastructure.”
Emphasize your background in AI observability and model evaluation pipelines
— “Experience with AI observability, model/application telemetry, prompt and model versioning, evaluation pipelines, and production quality monitoring.”
Demonstrate knowledge of Responsible AI and AI security practices in your application materials
— “Knowledge of Responsible AI, AI security, data privacy, model risk, prompt-injection mitigation, content safety, and enterprise AI governance.”

Pace · Fast PacedCollaboration · HighAutonomy · MediumDecision Impact · Team

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

design, develop, deploy, and own advanced AI/ML and Generative AI capabilities
translate complex business requirements into robust AI-powered solutions
mentor engineers and provide technical guidance on AI/ML architecture

Typical background

4+ years of hands-on AI/ML engineering experience4+ years of hands-on experience with modern AI/ML technologies5+ years of software engineering/programming experience

Skills & requirements

Required

Ai/ml EngineeringLarge Language Models (llms)Generative AIAgentic AIPrompt And Context-management StrategiesEmbeddingsVector DatabasesSemantic/hybrid SearchRerankingKnowledge-retrieval PipelinesCloud-native AI SolutionsCloud DeploymentModel/llm EvaluationAutomated TestingObservabilityPerformance OptimizationSecurityScalabilityCross-functional Technical DeliveryTechnical Leadership

Preferred

Technical Mentorship

Stack & domain

PythonC++JavaLarge Language Models (llms)Generative AIAgentic AIMachine LearningSoftware EngineeringPrompt And Context-management StrategiesEmbeddingsVector DatabasesSemantic/hybrid SearchRerankingKnowledge-retrieval PipelinesAI AgentsMulti-step AI WorkflowsTool/function CallingOrchestrationMemory/context ManagementIntegration With Enterprise Applications And Data SourcesCloud-native AI SolutionsAI ServicesApis/microservicesCloud DeploymentModel/llm EvaluationAutomated TestingObservabilityPerformance OptimizationSecurityScalabilityCross-functional Technical DeliverySoftware QualityCI/CDResiliencyMaintainabilityOperational ReadinessLeadershipCollaborationTechnical GuidanceMentorshipProblem-solvingCommunicationTechnical Trade-off AnalysisEngineering Best PracticesTechnical LeadershipTechnical ReviewFinanceHealthcare

About the role

Original posting from Honeywell

As an Advanced AI Software Engineer at Honeywell, you will design, develop, deploy, and own advanced AI/ML and Generative AI capabilities that power enterprise software applications and products. You will apply deep expertise in Large Language Models (LLMs), Generative AI, agentic AI, machine learning, and software engineering to build secure, scalable, reliable, and production-ready AI solutions.
You will provide technical leadership across the AI software development lifecycle, from architecture and experimentation through evaluation, deployment, observability, optimization, and production support. You will collaborate closely with software, product, data, cloud/platform, cybersecurity, and architecture teams to translate complex business requirements into robust AI-powered solutions.
You will report directly to our Director of Engineering, and you’ll work out of our Phoenix, Arizona location on a hybrid work schedule.
Note: For the first 90 days, new hires must be prepared to work onsite 100% M-F.
Key Responsibilities
Architect, design, develop, and deploy production-grade applications and software platforms using Large Language Models (LLMs), Generative AI, and agentic AI technologies.Design and implement advanced architectures, prompt and context-management strategies, embeddings, vector databases, semantic/hybrid search, reranking, and knowledge-retrieval pipelines.Build AI agents and multi-step AI workflows, including tool/function calling, orchestration, memory/context management, and integration with enterprise applications and data sources.Optimize AI workloads for latency, throughput, scalability, token consumption, infrastructure utilization, and cost.Design and implement cloud-native AI solutions and integrate AI services with existing enterprise applications, APIs, data platforms, and software architectures.Provide technical leadership in architecture reviews, design reviews, code reviews, technical trade-off analysis, and engineering best practices.Drive engineering standards for software quality, automated testing, CI/CD, security, scalability, resiliency, maintainability, and operational readiness.Collaborate with product and engineering teams to translate business problems into technically feasible AI solutions and measurable outcomes.Mentor engineers and provide technical guidance on AI/ML architecture, software engineering practices, troubleshooting, and production deployment.
YOU MUST HAVE
4+ years of hands-on AI/ML engineering experience, including designing, developing, deploying, and supporting AI/ML and Generative AI solutions in production environments.4+ years of hands-on experience with modern AI/ML technologies, including Large Language Models (LLMs), Generative AI, agentic AI prompt/context engineering, embeddings, vector databases, semantic/hybrid search, Transformers, and AI/ML frameworks.4+ years of experience architecting and delivering production AI/ML applications, including APIs/microservices, cloud deployment, model/LLM evaluation, automated testing, observability, performance optimization, security, scalability, and cross-functional technical delivery.5+ years of software engineering/programming experience, with strong hands-on proficiency in Python and experience with at least one additional programming language such as C++ or Java, developing scalable, maintainable, production-quality software.
WE VALUE
Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related technical field.Advanced experience with AI/ML frameworks and ecosystems such as PyTorch, TensorFlow, Hugging Face, LangChain, Semantic Kernel, or equivalent technologies.Experience with enterprise-grade vector databases and search technologies such as Azure AI Search, Elasticsearch, PostgreSQL/pgvector, Pinecone, or equivalent technologies.Experience with Azure AI services/Azure AI Foundry and/or Google Gemini/Vertex AI and cloud-based AI infrastructure.Experience with containerization and orchestration technologies such as Docker and Kubernetes.Experience building automated deployment pipelines using CI/CD, DevOps, Infrastructure as Code, and MLOps/LLMOps practices.Experience with AI observability, model/application telemetry, prompt and model versioning, evaluation pipelines, and production quality monitoring.Knowledge of Responsible AI, AI security, data privacy, model risk, prompt-injection mitigation, content safety, and enterprise AI governance.
BENEFITS OF WORKING FOR HONEYWELL
In addition to a competitive salary, leading-edge work, and developing solutions side-by-side with dedicated experts in their fields, Honeywell employees are eligible for a comprehensive benefits package. This package includes employer subsidized Medical, Dental, Vision, and Life Insurance; Short-Term and Long-Term Disability; 401(k) match, Flexible Spending Accounts, Health Savings Accounts, EAP, and Educational Assistance; Parental Leave, Paid Time Off (for vacation, personal business, sick time, and parental leave), and 12 Paid Holidays. Learn more (https://benefits.honeywell.com/)
The application period for the job is estimated to be 40 days from the job posting date; however, this may be shortened or extended depending on business needs and the availability of qualified candidates. Job Posted: October 14, 2026
About Honeywell Technologies
Honeywell Technologies is a global, pure-play automation company with a legacy of innovating to help solve the world’s most mission-critical challenges, enhancing the quality of life for people and communities around the world. We serve the building, industrial, and process sectors with a broad portfolio of services, solutions, and products, underpinned by our Honeywell Technologies Accelerator operating system and Honeywell Technologies Forge intelligence layer. By combining the deep domain expertise of our more than 50,000 employees with decades of data from our global installed base, we are uniquely positioned to lead the industrial sector’s transition from automation to autonomy.
THE BUSINESS UNIT
Honeywell Technologies Process Automation helps customers run complex industrial operations more safely, efficiently, and reliably. From automation and control systems to cybersecurity, digital solutions, and operational optimization, we enable critical industries to improve performance, reduce risk, and achieve their sustainability objectives.
Honeywell Technologies is a global, pure-play automation company with a legacy of innovating to help solve the world’s most mission-critical challenges, enhancing the quality of life for people and communities around the world. We serve the building, industrial and process sectors with a broad portfolio of services, solutions and products, underpinned by our Honeywell Technologies Accelerator operating system and Honeywell Technologies Forge intelligence layer. By combining the deep domain expertise of our more than 50,000 employees with decades of data from our global installed base, we are uniquely positioned to lead the industrial sector’s transition from automation to autonomy.

Source: Honeywell careers