TECHNICAL ARCHITECT AI, AGENTIC AI & ENTERPRISE TRANSFORMATION

ROLE OVERVIEW

We are looking for an experienced Technical Architect to lead the architecture and delivery of enterprise-wide AI enablement, Agentic AI, automation, data/knowledge platforms, and internal transformation initiatives.

The ideal candidate will have 712 years of technology experience with robust hands-on expertise in AWS, Python, AI/Agent development, automation, and data integration.

This is a hands-on architecture and technology leadership role requiring the ability to translate business transformation opportunities into scalable technical solutions and lead development teams through end-to-end implementation.

The role will work closely with multiple functions in a matrix-based organization and requires regular in-office presence and close collaboration with business, technology, data, operations, and transformation teams.

KEY RESPONSIBILITIES

1. SOLUTION & TECHNICAL ARCHITECTURE

- Own the architecture and technical design of internal enterprise transformation solutions across AI, Agentic AI, automation, data platforms, and knowledge management.
- Design scalable, secure, maintainable, and reusable solutions using AWS cloud technologies.
- Define architecture patterns and engineering standards for AI Agents, multi-agent workflows, automation platforms, APIs, data stores, and knowledge stores.
- Evaluate technology choices and make architecture decisions considering scalability, security, integration, cost, maintainability,



and enterprise standards.
- Remain sufficiently hands-on to develop prototypes, validate architecture decisions, troubleshoot complex technical issues, and guide engineering teams.

1. AGENTIC AI & AI ENABLEMENT

- Architect and build AI Agents and Agentic AI applications for enterprise use cases.
- Design agent workflows involving reasoning, tool usage, APIs, enterprise data, knowledge retrieval, orchestration, and human-in-the-loop processes.
- Build solutions integrating LLMs with enterprise applications, databases, APIs, document repositories, and knowledge stores.
- Establish reusable frameworks and patterns for accelerating AI adoption across internal functions.
- Implement appropriate controls around security, access, observability, auditability, reliability, and responsible AI usage.
- Drive practical AI enablement initiatives that move from experimentation and prototypes into production-grade enterprise solutions.

1. AWS & PYTHON ENGINEERING

- Provide strong hands-on technical leadership across relevant AWS services and cloud-native architecture.
- Develop and review production-quality solutions using Python.
- Design cloud architectures covering compute, storage, APIs, integration, security, monitoring, data processing, and AI workloads.
- Establish engineering best practices around code quality, testing, CI/CD, deployment, monitoring, and operational support.
- Guide teams on appropriate use of serverless, contain

📌 Walk-in || Technical Architect: AI, Agentic Automation & Enterprise Transformati (Chennai)
🏢 BaseBiz
📍 Chennai