13 hours ago
Responsibilities
- Design and build reusable enterprise platform capabilities for developing, deploying, and operating AI agents and multi-agent workflows.
- Create frameworks, APIs, SDKs, libraries, templates, and reference implementations that connect agents securely to enterprise APIs, data, tools, applications, and knowledge sources.
- Develop orchestration, RAG, document ingestion, retrieval, vector or semantic search, grounding, citation, contextual enrichment, and agent memory capabilities.
- Build systematic evaluation for agent and LLM task success, response quality, grounding, tool-use correctness, latency, reliability, and cost.
- Implement end-to-end observability, tracing, monitoring, alerting, and diagnostics across agents, models, tools, retrieval systems, APIs, and platform services.
- Design and operate cloud-native AI platform services supporting deployment, configuration, versioning, experimentation, evaluation, and lifecycle management.
- Build automated CI/CD and testing pipelines and convert prototypes and notebooks into modular, testable, maintainable production software.
- Implement guardrails, access controls, auditability, human oversight, retries, timeouts, degraded-dependency handling, and other safety and reliability mechanisms.
- Optimize AI workloads for latency, throughput, infrastructure utilization, and model or token cost.
- Collaborate with data engineers, AI/ML engineers, application teams, architects, product teams, and domain experts to productionize emerging AI capabilities.
Requirements
- 8+ years of software, data platform, ML platform, or AI engineering experience designing, building, and supporting production-grade systems.
- Strong Python software engineering expertise, including API and service development, testing, debugging, packaging, design patterns, and modern development practices.
- Experience building cloud-native distributed applications and platforms using containers, Kubernetes, public cloud technologies, CI/CD pipelines, observability, and reliability engineering.
- Hands-on experience developing and deploying AI/ML and generative AI solutions, including model serving, lifecycle management, monitoring, operational support, and production deployments.
- Experience building LLM and agentic AI applications involving RAG or grounding, enterprise data integration and retrieval, orchestration frameworks, and tool or API integration.
- Experience with LangGraph, LangChain, Semantic Kernel, AutoGen, or equivalent agent orchestration frameworks is valued.
- Experience with multi-agent systems, tool ecosystems, planning or reasoning workflows, agent memory, or human-in-the-loop patterns is valued.
- Experience with AI evaluation and observability platforms such as LangSmith and MLflow is valued.
- Experience with Azure Machine Learning, Azure AI services, Databricks, Kubernetes, or comparable AI and data platforms is valued.
- Experience with vector databases, semantic search, knowledge graphs, RDF/SPARQL, Neo4j, ontology engineering, or GraphRAG-style systems is valued.
- Experience integrating AI systems with industrial IoT, operational technology, building systems, digital twins, or high-volume telemetry is valued.
- Experience building developer platforms, SDKs, internal frameworks, or reusable engineering capabilities for multiple development teams is valued.
- Bachelor's or advanced degree in Computer Science, Engineering, Artificial Intelligence, or a related discipline, or equivalent practical experience.
Benefits
- Comprehensive benefits include employer-subsidized medical, dental, vision, and life insurance; short- and long-term disability; 401(k) match; flexible spending and health savings accounts; EAP; educational assistance; parental leave; paid time off; and 12 paid holidays.
- The role is based in Atlanta, Georgia, on a hybrid basis, with 100% onsite work Monday through Friday required for the first 90 days.
- The application period is estimated at 40 days from the October 26, 2026 posting date, subject to business needs and candidate availability.
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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.