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

UPS Supply Chain Solutions, Inc.; India; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

UPS Supply Chain Solutions, Inc. seeks an accomplished AI Application Architect to design and deliver enterprise-scale AI and GenAI systems.

This hands-on technical leader will define architectures for ML/GenAI on cloud platforms (GCP Vertex AI, AWS SageMaker, Azure ML) and drive adoption across the organization. You will mentor AI/ML engineers, collaborate with data scientists and business stakeholders, and ensure production-grade, secure, scalable solutions that create measurable business

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
• 7+ years designing, building, and deploying enterprise AI/ML solutions.
• Experience designing architectures for ML/GenAI workloads and production systems.

Responsibilities

• Architect and design ML/GenAI architectures on cloud platforms.
• Build, deploy, and maintain enterprise-scale AI apps that are secure and scalable.
• Lead adoption of emerging AI/GenAI technologies across the organization.
• Partner with product, engineering, and business teams to translate problems into AI solutions.
• Define end-to-end data pipelines, model development, deployment and monitoring.
• Promote best practices in MLOps, governance, and responsible AI.
• Provide technical leadership to AI/ML engineers and data scientists.
• Stay current with AI/LLM advances and cloud-native architectures.
• Define roadmaps to accelerate AI adoption across the enterprise.
• Collaborate with executives to advocate AI capabilities.

Skills

Python

Java

C++

PyTorch

TensorFlow

LLMs

ML Fundamentals

Communication

Education

Bachelor’s or Master’s degree in Computer Science/Engineering

Tools

GCP Vertex AI

AWS SageMaker

Azure ML

Kubeflow

MLflow

Job description

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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

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