Overview

We are looking for a Senior Enterprise AI Architect who has implemented GenAI/Agentic AI solutions on top of enterprise platforms such as SAP, Oracle, Salesforce, ServiceNow, PEGA .

Responsibilities

• Position Overview
• Tech Mahindra is hiring Senior AI Architects across Hyderabad, Chennai, Pune, and Bangalore. This role is for senior technology leaders who can define AI architecture strategy, design enterprise-grade solutions, and guide teams from concept to production at scale.
• The position combines strategic advisory responsibilities with hands-on architecture and implementation leadership. It is suited to professionals who can connect business priorities, enterprise platforms, cloud ecosystems, and AI engineering practices into scalable and reusable solution patterns.
• Role Purpose
• The Senior AI Architect will shape and validate AI-led transformation programs for enterprise clients, with a strong focus on scalable architecture, reusable assets, and outcome-driven solution design. The role is expected to bridge business stakeholders, enterprise architects, platform teams, data and AI engineering teams, and delivery leadership across global engagements.
• This role requires practical judgment on how AI should be embedded into enterprise landscapes, including business applications, integration layers, governance controls, and production operations. Strong communication with CXOs and cross-functional stakeholders is central to success in this role.
• Define target-state AI and data architecture aligned to business outcomes, enterprise architecture standards, and transformation roadmaps.
• Design end-to-end AI solution architectures covering data pipelines, model development, deployment, monitoring, security, and integration with enterprise applications.
• Build scalable and reusable assets, accelerators, reference architectures, frameworks, and patterns for enterprise AI adoption.
• Evaluate and validate solution options across cloud, AI, and enterprise application platforms such as SAP, Oracle, ServiceNow, and Salesforce.
• Lead architecture reviews, technical due diligence, feasibility studies, and proof-of-concept direction for AI initiatives.
• Collaborate with business leaders, delivery teams, product owners, security teams, and global stakeholders to shape credible and implementable solutions.
• Establish good practices for testing, deployment, observability, lifecycle management, and production support of AI systems.
• Drive architectural governance across responsible AI, compliance, privacy, model risk, and enterprise security requirements.
• Mentor engineering and architecture teams, influence critical technology choices, and support executive-level solution positioning.
• 12+ years of overall experience in enterprise technology, architecture, or digital transformation, with strong recent experience in AI/ML solution architecture and delivery.
• Proven hands-on experience designing and implementing production-grade AI or ML solutions for enterprise use cases.
• Experience across more than one enterprise platform, preferably SAP, Oracle, ServiceNow, Salesforce, or adjacent enterprise ecosystems.
• Experience working in architecture consulting, transformation programs, or complex enterprise modernization engagements.
• Demonstrated ability to work with CXOs, business stakeholders, and multidisciplinary global teams to influence architectural decisions.
• Strong understanding of enterprise integration patterns, API-led architecture, security, scalability, and non-functional design principles.
• End-to-end AI/ML architecture, including data ingestion, feature engineering, training pipelines, model serving, monitoring, and lifecycle management.
• Experience with generative AI architecture, including LLM-based applications, retrieval-augmented generation, prompt orchestration, guardrails, and evaluation patterns.
• Ability to define reference patterns for recommendation, forecasting, NLP, computer vision, intelligent automation, and enterprise copilots.
• Strong architecture experience on one or more cloud platforms such as AWS, Microsoft Azure, or Google Cloud.
• Working knowledge of enterprise MLOps and LLMOps practices such as experiment tracking, model registry, pipeline orchestration, deployment automation, and model monitoring.
• Experience with tools and platforms such as Azure Machine Learning, Amazon SageMaker, Vertex AI, Databricks, MLflow, Kubeflow, DVC, Airflow, or equivalent ecosystems.
• Hands-on familiarity with Python and common AI/ML frameworks such as TensorFlow, PyTorch, scikit-learn, LangChain, LlamaIndex, Hugging Face, or similar tools used in enterprise AI delivery.
• Understanding of vector databases, knowledge retrieval patterns, API orchestration, agent frameworks, and model integration approaches for production AI systems.
• Experience integrating AI services with enterprise applications, data platforms, and middleware layers using secure and scalable design patterns.

Education

• AWS, Azure, or Google Cloud architecture certifications.
• AI/ML specialty certifications on major cloud platforms.
• Enterprise architecture or platform certifications across SAP, Oracle, ServiceNow, Salesforce, or related ecosystems.
• Bachelor's degree in computer science, Engineering, Information Technology, or a related discipline is required. A master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field is preferred.