3 days ago
Responsibilities
- Architect, develop, deploy, and support production-grade AI/ML, Generative AI, and agentic AI applications and platforms.
- Design prompt and context-management strategies, embeddings, vector databases, semantic and hybrid search, reranking, and knowledge-retrieval pipelines.
- Build AI agents and multi-step workflows using tool/function calling, orchestration, memory and context management, and enterprise integrations.
- Optimize AI workloads for latency, throughput, scalability, token consumption, infrastructure utilization, and cost.
- Design cloud-native AI solutions integrated with enterprise applications, APIs, data platforms, and software architectures.
- Provide technical leadership in architecture, design, code reviews, technical trade-off analysis, and engineering practices.
- Drive standards for software quality, automated testing, security, scalability, resiliency, maintainability, and operational readiness.
- Collaborate with product and engineering teams to translate business requirements into measurable AI solutions.
- Mentor engineers and provide technical guidance on AI/ML architecture, software engineering, troubleshooting, and production deployment.
Requirements
- At least four years of hands-on AI/ML engineering experience designing, developing, deploying, and supporting production AI/ML and Generative AI solutions.
- At least four years of hands-on experience with LLMs, Generative AI, agentic AI, prompt and context engineering, embeddings, vector databases, semantic and hybrid search, Transformers, and AI/ML frameworks.
- At least four years of experience architecting and delivering production AI/ML applications involving APIs, microservices, cloud deployment, model and LLM evaluation, automated testing, observability, performance optimization, security, scalability, and cross-functional technical delivery.
- At least five years of software engineering or programming experience, including strong proficiency in Python and experience with C++ or Java.
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related technical field is valued.
- Preferred experience includes PyTorch, TensorFlow, Hugging Face, LangChain, Semantic Kernel, Azure AI Search, Elasticsearch, PostgreSQL/pgvector, Pinecone, Azure AI services, Azure AI Foundry, Google Gemini, Vertex AI, Docker, Kubernetes, AI observability, telemetry, prompt and model versioning, evaluation pipelines, Responsible AI, AI security, data privacy, model risk, prompt-injection mitigation, content safety, and enterprise AI governance.
Benefits
- Comprehensive medical, dental, vision, and life insurance, plus short-term and long-term disability coverage.
- 401(k) match, Flexible Spending Accounts, Health Savings Accounts, Employee Assistance Program, and educational assistance.
- Parental leave, paid time off, and 12 paid holidays.
- Hybrid work schedule in Phoenix, Arizona, with a requirement to work onsite Monday through Friday for the first 90 days.
- The application period is estimated at 40 days from the October 14, 2026 posting date, subject to business needs and candidate availability.
Tech Stack
Categories
About Honeywell
Honeywell is a public industrial technology company that sells aerospace systems, industrial automation, warehouse and building management technologies, and safety and security products to commercial, industrial, and government customers. Its portfolio spans avionics and propulsion, process controls and SCADA, warehouse automation, and IoT software such as Honeywell Forge. The company is headquartered in Charlotte, North Carolina and serves global markets across aviation, energy, logistics, and critical infrastructure.