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Trane Technologies

Global HVAC and refrigeration efficiency solutions

Data & AI Delivery Leader

Applied Machine Learning +1Confirmed live in the last 24 hours
Full-timeNo salary listed

About the Job

Requirements

  • A bachelor's or master's degree in Computer Science, Information Technology, Data Engineering, Software Engineering, Artificial Intelligence, or a related technical field is required.
  • At least 10 years of experience in solution architecture, data architecture, enterprise data platforms, analytics delivery, AI solution design, or related technology leadership roles is required.
  • Strong experience leading end-to-end solution design and delivery for complex data, analytics, and AI initiatives in enterprise environments is required.
  • Deep understanding of cloud data platforms, preferably Google Cloud Platform or BigQuery, or equivalent enterprise cloud ecosystems is required.
  • Strong expertise in data architecture, data modelling, semantic design, analytical solution patterns, and governed data foundations is required.
  • Practical experience designing or leading enterprise AI solutions, including generative AI, knowledge retrieval, AI assistants, or machine-learning-enabled decision-support capabilities is required.
  • Ability to balance enterprise data platform thinking with AI solution delivery and business adoption is required.
  • Experience guiding cross-functional teams across architecture, engineering, analytics, governance, security, and business stakeholders is required.
  • Strong understanding of data governance, metadata, lineage, quality, security, responsible AI, and enterprise standards is required.
  • Strong communication, leadership, stakeholder management, and decision-making skills, including the ability to operate effectively in ambiguity and lead through change, are required.

Responsibilities

  • Own end-to-end architecture for Data and AI solutions aligned to enterprise strategy, business goals, and platform standards while remaining hands-on in key solution areas.
  • Define scalable, secure, and reusable architecture patterns across data ingestion, transformation, modelling, semantic layers, analytics, AI/ML, and generative AI components.
  • Translate business capability needs into architecture blueprints, technical decisions, and implementation direction.
  • Lead delivery execution across product, engineering, governance, security, and business teams from concept through implementation, maintaining a reasonable level of direct involvement in solution shaping and critical execution decisions.
  • Shape new initiatives by defining scope, sequencing, dependencies, risks, assumptions, and high-level estimates.
  • Drive architecture and delivery decisions across multiple concurrent efforts while balancing speed, quality, risk, sustainability, and value realization.
  • Guide data architecture across cloud-native platforms, including lake, warehouse, semantic, and consumption layers, and ensure governed, reusable data models align with business definitions.
  • Lead design and delivery of enterprise AI solutions, including generative AI, retrieval-augmented generation, enterprise AI assistants, knowledge retrieval, intelligent workflow automation, and predictive analytics use cases.
  • Establish practical delivery and evaluation patterns for AI solutions from experimentation through production rollout, monitoring, and continuous improvement.
  • Ensure solutions meet enterprise standards for governance, security, privacy, responsible AI, operational readiness, and supportability.
  • Act as a key interface across business stakeholders, product leaders, governance leaders, engineering teams, and enterprise technology leadership, while building team capability through mentoring, coaching, and practical knowledge transfer.

Desired Qualifications

  • Experience supporting enterprise AI assistants, retrieval-augmented generation, knowledge retrieval, or similar Data and AI solution patterns.
  • Experience defining AI governance guardrails, model risk controls, or responsible AI practices in an enterprise setting.
  • Familiarity with metadata, data catalog, governance, vector search, or knowledge platform capabilities.
  • Experience with Git-based delivery practices, DevOps, continuous integration/continuous delivery, and modern engineering standards for data and AI platforms.
  • Exposure to domain-oriented data product principles and federated delivery models.
  • Experience helping scale AI adoption through reusable patterns, playbooks, delivery frameworks, or platform enablement.

About the Company

Trane Technologies

Global HVAC and refrigeration efficiency solutions

Trane Technologies focuses on climate innovation by delivering sustainable HVAC and refrigeration solutions through its Trane and Thermo King brands. It helps buildings, homes, and transportation achieve higher energy efficiency with high-performance climate control equipment and ongoing maintenance services. The company differentiates itself by offering an integrated portfolio of energy-efficient products and service contracts across both HVAC and refrigeration, backed by a commitment to sustainability. Its goal is to lower energy use and carbon emissions for customers while supporting a healthier planet.

Company size
10,001+
Company stage
IPO
Headquarters
Dublin, Ireland
Founded
1871

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