AI Solution Architect

Role: Solution Architect

Required Skills: Artificial Intelligence

Experience: 12 - 15 Years

Function: TECHNOLOGY

Apply By: 2026-12-26

Must Have Technical/Functional Skills

Role Summary

We are seeking an experienced AI Solution Architect to design, architect, and deliver scalable, secure, and enterprise-ready AI solutions aligned with business objectives. The role will translate business requirements into technical architectures, lead AI solution design, and

collaborate with engineering, data, cloud, security, and business teams to deliver production-grade AI capabilities.

The ideal candidate has strong expertise in enterprise architecture, cloud platforms, AI/ML technologies, and Generative AI solutions, with the ability to drive technical decisions from conceptual design through implementation and production deployment.

Required Skills

• Strong experience in solution architecture, enterprise application architecture, or AI/ML engineering.
• Hands-on experience designing and delivering AI/ML or Generative AI solutions.
• Strong understanding of LLMs, RAG, AI agents, prompt engineering, and model evaluation.
• Experience with Python and AI/ML frameworks such as PyTorch, TensorFlow, or equivalent.
• Experience with cloud platforms such as AWS, Azure, or GCP.
• Understanding of APIs, microservices, data pipelines, databases, and enterprise integration patterns.
• Knowledge of AI security, data privacy, governance, and responsible AI practices.
• Strong communication, stakeholder management, problem-solving, and technical leadership skills.
• Experience implementing enterprise AI solutions in production environments.
• Familiarity with vector databases, embeddings, semantic search, and orchestration frameworks.
• Experience with MLOps, CI/CD, model monitoring, and cloud infrastructure automation.
• Experience with enterprise platforms such as Salesforce, SAP, ServiceNow, or other business applications.
• Relevant cloud architecture or AI certifications.

Roles & Responsibilities

Key Roles and Responsibilities

1.AI Solution Architecture and Design

oDefine end-to-end architecture for enterprise AI, machine learning, and Generative AI solutions.

oTranslate business requirements and use cases into scalable, secure, and maintainable technical designs.

oEvaluate and recommend appropriate AI models, frameworks, platforms, and technology components.

oDevelop architecture diagrams, solution blueprints, technical specifications, and design documentation.

2.Generative AI and Agentic AI

oDesign and implement solutions using Large Language Models (LLMs),

Retrieval-Augmented Generation (RAG), AI agents, and intelligent automation.

oDefine prompt engin eering strategies, orchestration patterns, tool integrations, and workflow automation.

oEstablish appropriate AI guardrails, human-in-the-loop controls, and mechanisms to reduce hallucinations.

oEvaluate model performance, accuracy, relevance, latency, and cost.

3.Cloud and Platform Architecture

oArchitect AI solutions on cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform.

oDesign integrations with enterprise applications, APIs, databases, data platforms, and cloud-native services.

oDefine infrastructure, scalability, availability, performance, and disaster recovery requirements.

oRecommend appropriate deployment approaches, including cloud, hybrid, and on-premises environments.

4.Data Architecture and Integration

oDefine data ingestion, transformation, processing, storage, and retrieval strategies for AI solutions.

oDesign data pipelines and integration patterns to support AI and machine learning applications.

oEnsure data quality, lineage, governance, and access controls.

oCollaborate with data engineering teams to establish reliable and reusable data foundations.

5.Security, Governance, and Responsible AI

oIncorporate enterprise security, privacy, and regulatory requirements into AI architecture.

oDefine controls for sensitive data, personally identifiable information (PII), access management,

and secure model interactions.

oEstablish AI governance practices covering model usage, evaluation, monitoring, and risk management.

oEnsure solutions align with enterprise architecture and technology standards.

6.Technical Leadership and Delivery

oProvide architectural guidance and technical leadership to development, data, and AI engineering teams.

oReview solution designs, code, integrations, and implementation approaches for architectural alignment.

oSupport proof of concepts (PoCs), prototypes, and technical feasibility assessments.

oResolve complex technical issues and guide teams through implementation and deployment.

oCollaborate with product owners, business stakeholders, and delivery teams to ensure solutions meet business and technical expectations.

7.Performance, Monitoring, and Optimization

oDefine performance benchmarks and success criteria for AI solutions.

oEstablish monitoring for model quality, response accuracy, latency, availability, and operational costs.

oOptimize AI architecture for scalability, reli ability, and cost efficiency.

oSupport continuous improvement based on production feedback and evolving business needs.

8.Stakeholder Engagement and Innovation

oEngage with business stakeholders to identify AI opportunities and assess business value.

oPresent solution architectures, technical recommendations, and trade-offs to technical and

executive audiences.

oStay current with emerging AI technologies, frameworks, and industry best practices.

oIdentify opportunities to standardize, reuse, and accelerate enterprise AI capabilities.

Generic Managerial Skills:

-Strong stakeholder management and ability to communicate confidently with senior client and TCS leadership.

-Sound decision-making and risk-management judgment under time pressure, particularly during CAB and emergency change scenarios.

Salary Range: $180,000-$220,000 a year