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

UPS; Chennai District; On-site; INR 2,000,000 - 2,500,000; Full time

Job summary

A leading logistics company is seeking an accomplished AI Application Architect to design and deliver enterprise-scale AI systems. You will define architectures for ML/GenAI solutions on cloud platforms and lead the adoption of emerging technologies. Ideal candidates have over 7 years of experience in AI/ML, strong programming skills, and the ability to lead cross-functional teams. This role offers a dynamic environment to shape the future of AI within the organization.

Qualifications

• 7+ years of experience designing AI/ML solutions.
• Proven experience in building enterprise-grade architectures for ML/GenAI workloads.
• Deep understanding of ML/AI fundamentals.

Responsibilities

• Architect and design application architectures for ML/GenAI solutions.
• Lead research and adoption of emerging AI technologies.
• Define end-to-end architecture for data pipelines.

Skills

Cloud platforms expertise

Programming skills in Python, Java, or C++

Knowledge of ML/AI frameworks

Understanding of MLOps practices

Excellent communication skills

Education

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

Tools

GCP, Vertex AI

AWS SageMaker

Azure ML

MLflow

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.

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.