FREE ACCESS
5,000–10,000 jobs/day
See all jobs on Scoutfield
Search thousands of fresh jobs every day.
Discover
- Fresh listings
- Fast filters
- No subscription required
Create a free account and start exploring right away.
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in leading the design and deployment of AI solutions, with a strong focus on governance, evaluation, and operational excellence. Proficient in collaborating across engineering disciplines to deliver high-value AI applications and drive innovation in product development.
Highest-signal resume keywords
Artificial Intelligence LeadershipMachine Learning ExpertiseData Analytics ProficiencyAI Solution DevelopmentMLOps Knowledge
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Artificial IntelligenceMachine LearningData AnalyticsData EngineeringPredictive InsightsAgent OrchestrationPrompt EngineeringLarge Language ModelsContinuous Integration/Continuous DeploymentFault Detection
Soft Skills
Technical LeadershipCollaborationMentoring
Tools & Technologies
AWSAzureVector DatabasesSemantic SearchRetrieval-Augmented Generation
Certifications & Qualifications
Master's DegreePh.D.
Industry Keywords
HVACRefrigerationEngineering Product DevelopmentSystems EngineeringDigital Engineering
Tech Stack
Tools & technologiesAWSAzure
About the role
Key responsibilities & impact- Lead the design, development, deployment and governance of AI solutions for business units and center of excellence teams
- Lead AI technical solution design for aftermarket, AI-integrated products and AI-powered engineering processes
- Define and execute the AI strategy, roadmap, standards and best practices across Carrier Engineering
- Collaborate with software, systems, electrical, mechanical and business unit engineering teams to identify and deliver high-value AI solutions
- Establish governance, security, evaluation and responsible AI practices for enterprise AI deployments
- Lead proof-of-concepts, pilots/field trials and production deployments while ensuring measurable business impact and operational excellence
- Guide and mentor engineers and provide technical leadership in AI solution development, model evaluation and deployment
- Evaluate emerging AI technologies and drive adoption of innovative solutions across the engineering organization
Requirements
What you’ll need- Master's degree with 10+ years of industrial experience in Artificial Intelligence, Machine Learning, Data Analytics, Software Engineering or technical domains, or Ph.D. in Computer Science, Computer Engineering, Electrical Engineering, Artificial Intelligence, Data Science with 8+ years of industrial experience in Artificial Intelligence, Machine Learning, Data Analytics, Software Engineering or technical domains
- 5+ years of AI technical leadership work experience and engineering domain knowledge
- Willing and able to travel up to 10% annually, including both domestic and international trips
- Strong experience leading teams working on AI, Machine Learning, Data Analytics, or Agentic AI technologies
- Strong background in Artificial Intelligence, Machine Learning, Data Analytics, Data Engineering and software engineering
- Hands-on experience in delivering aftermarket fault detection and diagnostics, time-series forecasting and predictive insights/solutions
- Hands-on experience designing, developing, and deploying AI agents and agentic workflows to automate and accelerate engineering processes across the product development lifecycle
- Strong knowledge of agent orchestration, prompt engineering, planning, reasoning, memory management, tool calling, and Model Context Protocol (MCP) integrations
- Experience developing AI assistants and knowledge-based AI solutions using enterprise knowledge repositories, vector databases, embeddings, semantic search, and Retrieval-Augmented Generation (RAG) technologies
- Experience deploying enterprise AI solutions on AWS and/or Azure and integrating them with engineering tools, repositories, APIs, knowledge sources, and enterprise platforms
- Knowledge of AI evaluation, governance, and monitoring best practices, including Machine Learning Operations (MLOps), Large Language Model Operations and Continuous Integration/Continuous Deployment (CI/CD) pipelines for enterprise AI deployment
- Experience adapting, fine-tuning, and evaluating Large Language Models (LLMs) using enterprise and domain-specific data
- Experience in engineering product development, systems engineering, software engineering, electrical engineering, mechanical engineering, controls, simulation, or digital engineering
- Application experience in HVAC and refrigeration products
Benefits
Comp & perks- Short-term cash incentives, subject to plan requirements
- Medical, Dental, Vision
- Wellness incentives
- Retirement Benefits
- Paid vacation days, up to 15 days
- Paid sick days, up to 5 days
- Paid personal leave, up to 5 days
- Paid holidays, up to 13 days
- Birth and adoption leave
- Parental leave
- Family and medical leave
- Bereavement leave
- Jury duty leave
- Military leave
- Purchased vacation
- Short-term and long-term disability
- Life Insurance and Accidental Death and Dismemberment
- Health Savings Account
- Health Care Spending Account
- Dependent Care Spending Account
- Tuition Assistance