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We are seeking an experienced AI / Analytics Engineer to join Carrier's Global Data, Analytics & AI organization. This role is ideal for a hands-on engineer who combines a strong analytics foundation with modern AI/ML, GenAI, and Agentic AI engineering experience to develop scalable, business-critical solutions. The AI / Analytics Engineer will work closely with business stakeholders, product managers, and platform teams to understand business problems, translate them into data- and AI-driven solutions, and deliver production-ready capabilities that create measurable business value. This role requires an entrepreneurial mindset, the ability to move quickly from idea to solution, and a strong focus on building solutions that scale across functions, regions, and use cases.
Job Responsibility
Design, develop, and deploy analytics, AI/ML, GenAI, and Agentic AI solutions that address real business problems across functions such as Supply Chain, Manufacturing, Service, Marketing, and Commercial Operations
Build and maintain analytics engineering pipelines (data ingestion, transformation, semantic layers, feature engineering) to support advanced analytics and AI use cases
Develop and operationalize machine learning models (predictive, prescriptive, optimization) and GenAI solutions (e.g., RAG-based assistants, summarization, Q&A, copilots)
Design and implement Agentic AI workflows that orchestrate tools, data, and models to automate multi-step business processes with appropriate guardrails and human-in-the-loop controls
Partner with business stakeholders and product teams to understand requirements, frame problems, and identify opportunities where analytics and AI can drive impact
Translate ambiguous business needs into clear technical designs, data requirements, and solution architectures
Apply strong analytical thinking to define success metrics, validate assumptions, and continuously improve solutions based on outcomes
Collaborate with data platform, architecture, and security teams to ensure solutions align with enterprise standards, governance, and scalability requirements
Optimize models and pipelines for performance, reliability, cost, and scalability
Support production deployment and monitoring of analytics and AI solutions, including model performance, data quality, and system reliability
Contribute to best practices for MLOps / LLMOps, including versioning, testing, evaluation, and monitoring
Stay current with emerging trends in AI/ML, GenAI, Agentic AI, and analytics engineering, and proactively evaluate how new technologies can be applied at Carrier
Experiment, prototype, and iterate quickly—while designing solutions that can be scaled and reused across the enterprise
Promote responsible and ethical AI practices, including bias mitigation, transparency, and regulatory compliance
Requirements
Bachelor's degree in Computer Science, Data Science, Engineering, Business Analytics, or a related field
3-5 years of relevant experience in analytics engineering, data engineering, AI/ML engineering, or advanced analytics roles
Strong experience working with data analytics, data modeling, and large datasets in enterprise environments
Hands-on experience developing and deploying AI/ML models and analytics solutions
Proficiency in Python, SQL, and modern analytics or ML frameworks
Experience collaborating with business stakeholders and cross-functional teams