About the role

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.

• 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.

• 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.

• Hands-on experience with GenAI (e.g., RAG architectures, prompt engineering, LLM integration, evaluation frameworks).

• Exposure to or experience building Agentic AI solutions (tool-using agents, workflow orchestration, automation).

• Experience with modern data and analytics platforms such as Snowflake, Databricks, and visualization tools like Power BI.

• Familiarity with cloud platforms (AWS, Azure, or GCP).

• Experience applying Agile / product-oriented delivery models.

• Background in manufacturing, industrial, or HVAC domains is a plus.