Lead AI Platform & Automation Engineer (GCP, Vertex AI, Watsonx, MLFlow, Terraform)

About the role

UPS is looking for an accomplished AI Application Architect to join its AI Acceleration teams. The role designs and delivers enterprise-scale AI and Generative AI (GenAI) systems, defining application architectures for ML/GenAI solutions on cloud platforms such as GCP, Vertex AI and IBM Watsonx, and leading end-to-end design and implementation. It is a hands-on technical leadership position working with data scientists, ML engineers, software engineers and business stakeholders.

Key responsibilities

• Design application and system architectures for ML/GenAI solutions on cloud platforms and tools (GCP, Vertex AI, IBM Watsonx).
• Build, deploy and maintain enterprise-scale AI/ML applications that are production-ready, secure and scalable.
• Lead research and adoption of emerging AI/GenAI technologies, frameworks and tools at enterprise level.
• Partner with product, engineering and business teams to turn business challenges into AI/GenAI solutions.
• Define end-to-end architecture for data pipelines, model development, deployment, monitoring and retraining.
• Promote best practices in AI/ML system design, data governance, MLOps and responsible AI.
• Mentor AI/ML engineers and data scientists and stay current with AI/ML, GenAI, LLMs and cloud-native architecture.
• Define roadmaps that accelerate AI adoption and move the enterprise toward predictive and prescriptive analytics.
• Advocate AI/GenAI capabilities with executives and cross-functional leaders.

Required profile

• Bachelor's or Master's degree in Computer Science, Engineering or a related quantitative field.
• 7+ years of experience designing, building and deploying AI/ML solutions in production at enterprise scale.
• Proven experience designing enterprise-grade application architectures for ML/GenAI workloads.
• Strong programming skills in Python, Java or C++, and hands-on experience in one or more ML domains such as NLP, computer vision or reinforcement learning.
• Excellent communication and leadership skills, able to influence stakeholders and lead technical discussions.

Required skills

• Cloud platforms: GCP Vertex AI (preferred), AWS SageMaker or Azure ML.
• ML/AI frameworks: PyTorch, TensorFlow, Keras.
• MLOps tools: MLflow, TFX, Kubeflow, CI/CD pipelines, model monitoring.
• Preferred: experience leading research initiatives, cross-functional enterprise projects, and launching AI/GenAI solutions at scale; knowledge of GDPR, HIPAA and SOX.