Senior AI Architect

Location : Gurgaon | Hybrid

Experience : 10 - 12 Years

Duration : 12 Months Contract

Employment Type : FTE

Role Overview :

We are looking for a highly experienced Senior AI Architect to lead the architecture and design of enterprise-grade AI, LLM, and Agentic AI solutions. The ideal candidate will be a hands-on architect who can bridge Enterprise Architecture, Agentic AI, Context Engineering, LLM orchestration, and architecture governance. The role requires strong technical leadership, excellent architecture communication skills, and the ability to design scalable, secure, and enterprise-ready AI solutions.

Key Responsibilities :

- Lead the architecture and design of AI/LLM and Agentic AI solutions for enterprise environments.

- Define scalable and secure AI-native architectures aligned with business and technology objectives.

- Design MCP (Model Context Protocol) server architectures and agent-based systems.

- Architect solutions involving AI agents, RAG, tool use, prompt engineering, and LLM orchestration.

- Drive context engineering strategies to improve the reliability, relevance, and performance of AI applications.

- Evaluate and integrate LLM platforms, agent frameworks, APIs, and enterprise AI technologies.

- Establish architecture standards, patterns, and best practices across AI initiatives.

- Create and maintain Architecture Decision Records (ADRs) and ensure adherence to SDLC and security standards.

- Collaborate with engineering, product, security, and enterprise architecture teams to ensure effective solution delivery.

- Provide technical guidance on integrating AI solutions with enterprise ecosystems and platforms.

- Develop comprehensive architecture documentation, technical designs, and solution blueprints.

- Communicate complex technical concepts effectively to technical and business stakeholders.

- Ensure AI solutions comply with enterprise security, governance, scalability, and reliability requirements.

Must-Have Skills & Experience :

- 8+ years of experience in Software Architecture, Solution Architecture, or Enterprise Architecture.

- Strong hands-on experience with AI/LLM, Agentic AI, and AI-native architecture.

- Proven experience designing MCP (Model Context Protocol) server architectures.

- Strong understanding of Agent Architecture, Prompt Engineering, RAG, and Tool Use.

- Strong expertise in Context Engineering and LLM orchestration.

- Hands-on experience with at least 2 or more of the following :

1. MCP

2. LangChain / LangGraph

3. Claude API

4. OpenAI API

- Strong programming experience in Python and TypeScript/Node.js.

- Experience with architecture governance, ADRs, SDLC standards, and security frameworks.

- Experience working with enterprise ecosystems including Azure, GitHub, Jira, Confluence, and Salesforce.

- Excellent technical documentation, stakeholder management, and architecture communication skills.

Good to Have :

- Experience with agent runtimes, MCP servers, and managed agent platforms.

- Knowledge of Knowledge Graphs, Ontologies, and Semantic Architecture.

- Familiarity with enterprise architecture frameworks such as TOGAF or Zachman.

- Experience in consulting, research, or analytics environments.

- Experience designing and implementing enterprise-scale AI platforms and solutions.

Ideal Candidate :

The ideal candidate is a hands-on AI Architect who combines strong Enterprise Architecture expertise with deep knowledge of Agentic AI, LLMs, Context Engineering, MCP, and AI governance. The candidate should be capable of translating business requirements into scalable, secure, and production-ready AI architectures while effectively communicating with both technical and business stakeholders.