Lead AI Platform & Automation Engineer - GCP, Vertex AI, IBM Watsonx, MLFlow, Terraform
- Compensation
- Not disclosed
- Location
- IN - TDC 1 (IN110)
- Work setup
- Not specified
- Seniority
- Lead
- Employment
- Full time
- Experience
- 7+ years
- Category
- Industrial engineering
- Posted
Skills
Nice to have
- 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.
Full 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.