Sr. Director Data & AI Platforms

We are seeking a Senior Director of Forge Data, AI and Agent Platform wwho thrives at the intersection of deep platform engineering and forward-looking architecture strategy — a technologist who can design the systems that power AI at industrial scale today while anticipating what the next generation of AI‑native platforms will demand tomorrow.

You will define how data, AI models, and autonomous agents are architected across cloud, on‑premises, and hybrid edge environments. You will simplify complexity — turning a sprawling landscape of tools and capabilities into coherent, operable, and evolvable platforms. And you will be the connective force that brings together solution architects, engineering leaders, and business stakeholders into a unified strategy for growth of Forge AI for Honeywell Automation portfolio.

The Senior Director will be both strategic and hands‑on
, setting technical direction while mentoring senior architects and influencing executive stakeholders.

• Own and evolve the canonical reference architecture for the Industrial AI platform — spanning data ingestion, processing, model serving, and agentic orchestration layers.
• Define the architecture of the enterprise AI data platform including lakehouse, feature stores, vector databases, streaming pipelines, and real‑time inference infrastructure.
• Architect the agent platform: design the orchestration frameworks, tool registries, memory systems, and safety guardrails that enable reliable multi‑agent AI workflows at enterprise scale.
• Establish platform layering principles — separating concerns between infrastructure, platform services, AI capabilities, and application‑level solutions to ensure modularity and replaceability.
• Drive platform simplification initiatives: consolidate redundant tooling, reduce operational surface area, and establish "golden path" patterns that make building AI applications faster and more reliable.

• Maintain a continuous technology watch across AI platform, data engineering, agent frameworks, and edge computing domains — synthesizing signals from research, open‑source, and vendor communities into actionable architectural guidance.
• Lead structured evaluation of emerging technologies (new foundation model APIs, agentic frameworks, vector retrieval architectures, edge AI runtimes, next‑gen data formats) using rigorous PoC and architecture fitness criteria.
• Serve as the organization’s internal thought leader on platform evolution — publishing architecture decision records, technology briefings, and roadmap recommendations to CoE and enterprise leadership.
• Build relationships with hyperscaler architecture teams, AI platform vendors, and open‑source project leads to gain early visibility into emerging capabilities and influence platform direction.
• Identify and mitigate architectural technical debt proactively, proposing migration paths before legacy patterns constrain AI capability delivery.

• Design cloud‑native AI platform architectures on major hyperscalers including managed AI/ML services, serverless inference, cloud‑native data platforms, and AI gateway patterns.
• Architect for edge and near‑edge AI deployment patterns for industrial environments: model compression and optimization for edge hardware, OT/IT integration, edge inference orchestration, and edge‑to‑cloud data synchronization.
• Define hybrid architecture patterns that span cloud and on‑premises — addressing data residency requirements, network latency constraints, air‑gapped environments, and operational consistency across deployment tiers.
• Design for industrial‑grade reliability: architect patterns for fault tolerance, graceful degradation, offline operation, and deterministic failover in environments where downtime has direct operational consequences.
• Establish Fin Ops‑aligned architecture patterns that balance AI platform capability with cloud cost optimization across training, inference, and data processing workloads.

• Convene and lead the Forge Data and AI Architecture Forum across the enterprise with…