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Carrier is seeking a highly skilled and forward‑thinking AI & Data Solution Architect to lead the design, architecture, and delivery of enterprise‑scale Data, Analytics, and AI solutions across the organization. This role will play a critical part in defining enterprise data and AI architecture standards, shaping cloud‑first platforms, and enabling scalable, secure, and cost‑efficient adoption of analytics, machine learning, and generative AI.
Job Responsibility
Define and evolve Carrier’s AI & Data architecture strategy and roadmap, aligned with business priorities and IT strategy
Serve as a thought leader for modern data, analytics, and AI architectures, including Generative AI and Agentic AI
Identify, evaluate, and recommend emerging technologies, platforms, and architectural patterns
Partner with business and digital leaders to identify and prioritize high‑impact AI and analytics use cases
Provide architectural guidance on ethical, responsible, and compliant AI adoption
Lead end‑to‑end architecture design for complex data, analytics, and AI initiatives, ensuring scalability, performance, security, and cost efficiency
Design and govern cloud‑based data platforms leveraging: Google Cloud Platform (BigQuery, Vertex AI, Dataflow, Dataproc, Looker), AWS (S3, Glue, EMR, Redshift, SageMaker, Lambda), Snowflake (data warehouse, data sharing, performance optimization)
Architect modern enterprise data architectures, including: Data Lake, Lakehouse, Data Mesh, and Data Fabric, Open table/file formats such as Parquet, Iceberg, Delta Lake, Medallion architectures (Bronze/Silver/Gold)
Define data ingestion and integration patterns across structured and semi‑structured sources (SAP, Oracle, Salesforce, JDE, Ariba, IoT, APIs, NoSQL)
Define and enforce data quality, metadata, lineage, and access control standards
Design and implement AI/ML and GenAI solution architectures from experimentation through production
Architect solutions for core ML use cases such as demand forecasting, predictive maintenance, supply chain optimization, and customer analytics
Lead architecture for Generative AI and Agentic AI, including: LLM integration with tools, APIs, and knowledge bases (RAG patterns), Autonomous and semi‑autonomous agent workflows, Fine‑tuning, prompt engineering, and optimization strategies
Establish MLOps and LLMOps frameworks for model training, deployment, monitoring, evaluation, and lifecycle management
Define approaches for model observability, explainability (XAI), bias detection, and risk mitigation
Provide technical leadership and mentorship to solution architects, data engineers, data scientists, and AI engineers
Collaborate closely with platform, DevOps, and cloud engineering teams to enable automation‑driven deployments
Review solution designs, conduct architecture assessments, and provide impact analysis and recommendations
Communicate complex technical concepts clearly to both technical and executive audiences
Requirements
Bachelor’s Degree in engineering or technical discipline
8+ years hands‑on experience in data architecture, analytics solutions, and/or cloud data platforms
3+ years of hands‑on experience delivering AI/ML and Generative AI solutions in production
6+ years of experience designing and scaling enterprise data platforms on GCP, AWS, and Snowflake
Must have unrestricted authorization to work in the USA. No visa sponsoring available.
Nice to have
Master’s degree or Ph.D. preferred
Demonstrated success leading large‑scale, cross‑functional data and AI initiatives
Cloud platforms: GCP and AWS (multi‑cloud experience strongly preferred)
Data platforms: Snowflake, BigQuery, Data Lakes, Lakehouse architectures