Lead AI Platform & Automation Engineer - GCP, Vertex AI, IBM Watsonx, MLFlow, Terraform

UPS is hiring a Lead AI Platform & Automation Engineer - GCP, Vertex AI, IBM Watsonx, MLFlow, Terraform. Level rates it ; you can apply on UPS.

Level's read on this job

Builds AI ●●●● is how Level rates this role: the job is building AI systems.
Tools and skills the posting cites include Vertex AI, PyTorch and TensorFlow.
Level classifies it as a lead role.
Level lists 2,000+ other open roles at UPS.

AI in this role

Design and lead enterprise-scale AI and Generative AI application architectures on cloud platforms like GCP and Vertex AI.

Vertex AIPyTorchTensorFlowKerasMLflowSageMakerGoogle CloudIbm WatsonxTerraform

ml-opscomputer-visionnlpai-safetyartificial-intelligencemachine-learningenterprise-architecturemlopsgenerative-ai

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Job Description:

Job Summary

We are seeking an accomplished AI Application Architect to join our AI Acceleration teams and play a pivotal role in designing and delivering enterprise-scale AI and Generative AI (GenAI) systems. As an AI Architect, you will be responsible for defining application architectures for ML/GenAI solutions on cloud platforms & tools such as GCP, Vertex AI, IBM Watsonx, leading end-to-end design and implementation, and driving adoption of emerging technologies and frameworks across the organization.

This is a hands-on technical leadership role that requires deep expertise in AI/ML fundamentals, enterprise architecture design, and practical experience building production-grade AI/GenAI solutions. You will collaborate with data scientists, ML engineers, software engineers, and business stakeholders to deliver scalable, secure, and innovative AI-powered systems that create measurable business value.

Key Responsibilities

Architect and design application and system architectures for ML/GenAI solutions on cloud platforms, tools (GCP, Vertex AI, IBM Watsonx).
Build, deploy, and maintain enterprise-scale AI/ML applications, ensuring they are production-ready, secure, and scalable.
Lead research and adoption of emerging AI/GenAI technologies, frameworks, and tools at the enterprise level.
Partner with product, engineering, and business teams to translate business challenges into robust AI/GenAI solutions.
Define end-to-end architecture for data pipelines, model development, deployment, monitoring, and retraining.
Promote and evangelize best practices in AI/ML system design, data governance, MLOps, and ethical/responsible AI.
Provide technical leadership and mentorship to AI/ML engineers and data scientists across business units.
Stay current with advances in AI/ML, GenAI, LLMs, and cloud-native architecture, and identify opportunities for adoption.
Define roadmaps and strategies that accelerate AI adoption and help the enterprise transition from descriptive to predictive and prescriptive analytics.
Collaborate with executives and cross-functional leaders to advocate AI/GenAI capabilities and drive enterprise-wide adoption.

Required Qualifications

Bachelor’s or Master’s degree in Computer Science, Engineering, or a related quantitative field.

Experience

7+ years of experience designing, building, and deploying AI/ML solutions including monitoring, scaling, and optimization in production at enterprise scale.
Hands-on expertise in cloud platforms (GCP Vertex AI (preferred), AWS SageMaker, or Azure ML) and cloud-native application design.
Proven experience designing enterprise-grade application architectures for ML/GenAI workloads.
Strong programming skills in Python, Java, or C++, and proficiency with ML/AI frameworks (PyTorch, TensorFlow, Keras).
Deep understanding of ML/AI fundamentals: statistical modeling, architectures, representation, reasoning, and generative models (LLMs, diffusion).
Hands on experience in one or more ML domains such as NLP, computer vision, or reinforcement learning.
Hands on experience in MLOps practices and tools (MLflow, TFX, Kubeflow, CI/CD pipelines, model monitoring).
Strong knowledge of software architecture principles, cloud networking, and security best practices.
Excellent communication and leadership skills, with the ability to influence stakeholders and lead technical discussions across business and engineering teams.

Preferred

Experience leading research initiatives and driving enterprise-wide adoption of new technologies.
Experience with cross-functional enterprise projects, including scoping, de-risking, and scaling AI/GenAI adoption.
Knowledge of data governance, security frameworks, and regulatory compliance (GDPR, HIPAA, SOX).
Prior experience launching AI/GenAI solutions into production at scale using both open-source and vendor platforms.
Active involvement in the AI/ML community through publications, open-source contributions, or industry collaborations.

Employee Type:

Permanent

UPS is committed to providing a workplace free of discrimination, harassment, and retaliation.

How we rate this

Lead AI Platform & Automation Engineer - GCP, Vertex AI, IBM Watsonx, MLFlow, Terraform at UPS rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Lead AI Platform & Automation Engineer - GCP, Vertex AI, IBM Watsonx, MLFlow, Terraform is an open job at UPS.
Level rates this role AI Level 4 of 4: Builds AI.
The role is based in IN - TDC 1 (IN110).
The job was posted on June 29, 2026.
Seniority: lead.
Applications are handled by UPS. Apply on UPS

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

ML OpsComputer visionNLPAI SafetyArtificial IntelligenceMachine learningEnterprise ArchitectureMLOps

Questions you could be asked

How do you monitor a model once it's live, and how do you know it needs retraining?
Walk me through a computer vision problem you solved, from raw data to a deployed model.
What NLP problem have you worked on, and how did you measure whether it actually worked?
How do you think about the risk of an AI system in this kind of role failing silently?
Tell me about a project where artificial intelligence was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: ML Ops, Computer vision, NLP, AI Safety, and Artificial Intelligence. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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