Honeywell is embarking on a significant organizational transformation, undergoing a pivotal shift towards "Value by and with AI"—moving beyond simple chatbots to autonomous systems that reason, use tools, and execute end-to-end business workflows. We are standing up a dedicated “Digital Automation Hub” for GBS Finance in Bengaluru.
The AI Technical Program Manager (TPM) is a high-impact leadership role reporting to the Head of Digital Automation at GBS Finance. You will act as the primary bridge between Transformation, AI Research, Engineering, and Business Stakeholders. You are not just a coordinator; you are a technical supervisor of the AI Automation programs, ensuring that traditional AI and agentic AI workflows are designed for scalability, safety, and measurable ROI. You will own the Management Operating System (MOS) for our AI initiatives, translating complex model behaviours into transparent, predictable project milestones and managing stakeholder collaboration across GBS Finance (R2R, P2P, Commercial, ISC, FP&A and Corporate Finance).
Key Responsibilities
- Technical Governance: Establish the MOS for AI escalations, model performance drift, and high-impact system failures; provide proactive status reporting to leadership.
- SLA & KPI Ownership: Define and track unique AI (Model Drift, Accuracy, AUC-ROC, Precision-Recall) and Agentic AI metrics (e.g., Cost-per-Token, Agent Success Rate, Latency, and Accuracy) and coordinate gap-closure actions with data science teams.
- Stakeholder Synthesis: Act as the primary technical contact for Digital Automation catering to GBS Finance teams and rest of Honeywell Finance.
- Architectural Orchestration: Partner with engineering to design Traditional AI and Agentic system architectures, including multi-agent hand-offs, memory management, and tool-use protocols.
- Continuous Improvement: Leverage analytics to identify process bottlenecks and drive architectural improvements in the AI inference pipeline.
- Document Control: Maintain rigorous documentation for AI programs, model lineages, evaluation frameworks, and compliance standards.
You Must Have
- Experience: 15+ years of total experience in tech, with at least 5-7 years leading complex AI/ML programs in a Global Capability Centre (GCC) or high-growth product environment.
- The "Hybrid" Mindset: A rare mix of senior program leadership and the ability to "double-click" into technical system design.
- Education: Bachelor’s degree in Computer Science, Data Science, or a related technical field (Masters/MBA preferred).
- Technical Design Proficiency: Ability to lead "System Design" discussions and evaluate the trade-offs between different AI orchestration layers.
- ERP Ecosystem Literacy: Familiarity with high-scale ERP environments (SAP, Oracle) and how AI agents interface with legacy financial databases through APIs or RPA bridges.
- Deep AI Domain Expertise: Solid understanding of LLM lifecycles, Agentic frameworks (e.g., LangGraph, CrewAI, or AutoGen), and vector databases.
We Value
- Fiduciary Mindset: A background that respects the "zero-error" requirement of finance, balancing experimental AI with the rigor of global accounting standards.
- Influential Relationship Building: Ability to lead and collaborate across cross-functional pods (Data, DevOps, and Product).
- Strategic Problem Solver: Develops creative, compliant, and balanced solutions for probabilistic AI outcomes.
- Hands-on Pragmatism: An action-oriented leader who can navigate the ambiguity of emerging AI technologies without losing sight of delivery timelines.