Technical Program Manager — Digital Transformation & AI‑Enabled Operations
Role Overview
The Technical Program Manager (TPM) will lead large‑scale digital transformation initiatives focused on modernizing operational visibility, predictive analytics, and enterprise workflow automation across MRO, supply chain, and planning ecosystems. This role oversees end‑to‑end delivery of complex, multi‑stakeholder programs including AI/ML‑enabled alerting platforms, integrated data pipelines, cloud‑based dashboards, and workflow optimization tools.
The TPM acts as the connective tissue between engineering, data science, business operations, and leadership—ensuring alignment, removing ambiguity, and driving predictable execution across all program workstreams. The ideal candidate has deep experience leading digital transformations in data‑rich operational environments, orchestrating AI‑enabled products, and maturing organizations from manual, fragmented processes to fully integrated, predictive digital ecosystems.
Key Responsibilities
Program Leadership & Delivery
§ Lead planning, execution, and delivery of enterprise digital transformation initiatives, including AI/ML‑driven Early Warning Systems and operational alerting platforms. 1
§ Establish program roadmaps, milestones, and governance structures across engineering, data, business, and vendor partners.
§ Drive cross‑functional alignment, ensuring technical implementation meets business intent, operational workflows, and enterprise architecture standards.
§ Coordinate multiple agile development teams with iterative cycles, demos, and continuous stakeholder validation. 23
§ Identify risks, manage interdependencies, and lead root‑cause resolution across complex operational and technical domains.
Digital Transformation Execution
§ Translate fragmented legacy processes (spreadsheets, manual analysis, isolated systems) into unified, scalable, digital workflows. 1
§ Orchestrate transformation from rule‑based monitoring to predictive, AI‑enabled anomaly detection platforms leveraging machine learning and adaptive thresholds. 1
§ Drive current‑state vs. future‑state process mapping to ensure alignment with Digital Transformation objectives. 3
§ Champion automation opportunities, workflow redesign, and new operating models that improve decision‑making speed, accuracy, and predictability.
Technical Program Coordination
§ Work closely with data science teams to guide development of data pipelines, ML models, anomaly‑detection logic, and recommendation systems. 2
§ Align business rules, alert severity logic, and operational thresholds with engineering and model design decisions. 3
§ Ensure seamless integration of APIs, data services, dashboards, and backend components across cloud platforms.
Stakeholder & Vendor Management
§ Act as the primary interface between operational SMEs, supply chain leaders, engineering teams, and external partners.
§ Lead vendor engagement to ensure delivery of capabilities across MRP, planning, AI/ML, and supply chain domains as described in the enterprise Early Warning System roadmap.
§ Facilitate workshops, alignment sessions, and executive briefings with clear storytelling and impact‑driven communication.
Quality, Testing & Operational Readiness
§ Oversee UAT planning, prioritization, and defect management to ensure solution stability and business validation. 3
§ Drive operational readiness, training, change management, and transition‑to‑sustainment activities.
§ Establish performance metrics, monitoring frameworks, and continuous improvement cycles for AI/ML models and associated workflows
Required Skills & Experience
§ Proven track record leading enterprise digital transformation programs with multiple parallel technical workstreams.
§ Strong command of agile delivery methodologies, program governance, roadmapping, and cross‑functional coordination.
§ Experience delivering cloud‑based analytics products, dashboards, or AI‑enabled systems at scale.
Digital Transformation Expertise
§ Experience modernizing operational ecosystems from manual processes to automated, data‑driven, predictive workflows.
§ Deep understanding of MRO, supply chain, planning, or manufacturing data flows, KPIs, and exception logic.
Data, Analytics & ML Fluency
(Not as a practitioner, but as a technical orchestrator)
§ Familiarity with data engineering, ML model lifecycle, and platforms such as Databricks, Delta Lake, MLflow, and API‑based scoring frameworks. 2
§ Ability to translate analytical insights and model outputs into meaningful operational actions, workflows, and decision support mechanisms.
Business & Requirements Leadership
§ Ability to define alert logic, rules, severity scoring, and routing criteria that align with operational priorities. 3
§ Expertise transforming business requirements into technical execution plans, user stories, and acceptance criteria.
Communication & Stakeholder Skills
§ Excellent executive communication, ability to simplify complexity, and talent for aligning diverse stakeholders toward a unified vision.
Typical Deliverables
§ Program charters, governance frameworks, and multi‑release roadmaps.
§ End‑to‑end requirements, user stories, alert logic, and technical integration specifications.
§ Cross‑functional sprint plans, readiness assessments, and quality gates.
§ Stakeholder workshops, operational process maps, and future‑state transformation blueprints.
§ Executive dashboards summarizing progress, risks, KPIs, and impact.
§ Post‑launch adoption plans, continuous improvement loops, and performance monitoring frameworks.
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