Chief Agentic Architect
Summary
Leads modernization of legacy systems into AI-native platforms, defining architecture standards and overseeing AI agent orchestration for software development, testing, and deployment.
๐ง๐ต๐ถ๐ ๐ฟ๐ผ๐น๐ฒ ๐ถ๐ ๐ณ๐ผ๐ฟ ๐ผ๐ป๐ฒ ๐ผ๐ณ ๐๐ต๐ฒ ๐ช๐ฒ๐ฒ๐ธ๐ฑ๐ฎ๐'๐ ๐ฐ๐น๐ถ๐ฒ๐ป๐๐
๐ฆ๐ฎ๐น๐ฎ๐ฟ๐ ๐ฟ๐ฎ๐ป๐ด๐ฒ: ๐ฅ๐ ๐ฑ๐ฌ๐ฌ๐ฌ๐ฌ๐ฌ๐ฌ - ๐ฅ๐ ๐ฒ๐ฌ๐ฌ๐ฌ๐ฌ๐ฌ๐ฌ (๐ถ๐ฒ ๐๐ก๐ฅ ๐ฑ๐ฌ-๐ฒ๐ฌ ๐๐ฃ๐)
Experience: 14+ yrs
Location: Chennai, Tamil Nadu, India
Job Type: Full-time
We are looking for a highly experienced Chief Agentic Systems Architect to lead the transformation of large-scale legacy platforms into modern, scalable, AI-native engineering ecosystems. This senior architecture role combines software architecture, platform engineering, AI agent orchestration, modernization, and technical governance.
The role will focus on establishing architectural standards and engineering frameworks that enable AI agents to safely assist with software development, refactoring, validation, testing, and deployment. The ideal candidate will bring deep expertise in distributed systems and enterprise architecture, along with practical exposure to Agentic AI, LLM-based tooling, and AI-assisted software engineering.
Requirements
Key Responsibilities
- Define and drive the technical architecture strategy for modernizing large-scale legacy applications.
- Lead phased modernization initiatives using approaches such as the Strangler Pattern and contract-driven development.
- Establish scalable architectural principles based on SOLID, Dependency Injection, and Hexagonal Architecture.
- Design modular and AI-ready platforms that enable effective collaboration between engineering teams and autonomous AI agents.
- Define and manage agent context layers including Skills, Rules, Commands, and AI workflows.
- Develop and maintain Model Context Protocol (MCP) servers and AI-ready integration frameworks.
- Establish contract-first API strategies and governance across enterprise platforms.
- Review AI-generated code and architectural changes to ensure security, scalability, reliability, and maintainability.
- Establish and promote Test-Driven Development (TDD), characterization testing, and automated quality practices.
- Design frameworks for safe AI-assisted refactoring, testing, validation, and software delivery.
- Monitor and optimize AI agent workflows for reasoning quality, performance, reliability, and cost efficiency.
- Establish engineering standards, architectural guidelines, coding practices, and technical governance frameworks.
- Partner with engineering, product, security, and leadership teams to define long-term technology strategy.
- Identify technical risks, modernization dependencies, architectural bottlenecks, and opportunities for continuous improvement.
- Mentor senior engineers and architects and promote modern AI-native engineering practices across teams.
What Makes You a Great Fit
- 14+ years of experience in Software Architecture, Platform Engineering, Solution Architecture, or Technical Leadership.
- Strong hands-on expertise in TypeScript, .NET, and Node.js.
- Proven experience modernizing complex, large-scale legacy applications into modular and scalable platforms.
- Deep understanding of distributed systems, enterprise architecture, modular design, and scalable software engineering.
- Strong experience with API architecture, contract-first development, and enterprise integrations.
- Practical understanding of AI-assisted software development, LLM tooling, engineering automation, and Agentic AI systems.
- Experience with Model Context Protocol (MCP) or similar AI integration and orchestration frameworks is highly desirable.
- Strong knowledge of software quality, automated testing, TDD, CI/CD, and engineering governance.
- Ability to evaluate and govern AI-generated code and ensure production-grade engineering standards.
- Strong understanding of AI agent orchestration, context management, workflows, and autonomous engineering systems.
- Excellent problem-solving and systems-thinking capabilities.
- Strong communication and stakeholder management skills with the ability to influence technical strategy at an organizational level.
- Proven ability to lead engineering transformation and modernization programs.
- Experience working with geographically distributed engineering teams is an advantage.
- Exposure to SaaS transformation, high-growth technology organizations, or scale-up environments is preferred.
- Familiarity with AI-native software development practices and emerging agentic engineering technologies.