AI Architect

Zensar Technologies Limited seeks an experienced AI Architect to define and execute the architectural vision for its internal AI platform. You will create production‑grade multi‑agent frameworks, secure Model Context Protocol services, and robust RAG pipelines, while establishing engineering standards and mentoring teams to drive high‑throughput, low‑latency AI applications across the enterprise.

• Design and implement multi‑agent orchestration frameworks for autonomous negotiation, task delegation, and state management.
• Architect and develop scalable Model Context Protocol (MCP) servers and clients for secure LLM integration with data sources and enterprise tools.
• Define the architectural vision for Zensar's internal AI platform, ensuring high throughput, low latency, and seamless developer workflows.
• Write production‑ready code, build prototypes, and establish engineering best practices for AI application development.
• Standardize architectural patterns across the organization and author comprehensive RFCs.
• Mentor junior engineers and foster a culture of technical excellence.
• Collaborate with product, security, and operations teams to align AI solutions with business goals.
• Evaluate and integrate emerging AI SDKs, vector databases, and Retrieval‑Augmented Generation (RAG) pipelines.
• Drive performance tuning, scalability testing, and reliability engineering for AI services.
• Communicate complex technical concepts clearly to both technical and non‑technical stakeholders.

• 10+ years of software architecture experience, with at least 3 years building production‑grade LLM applications.
• Deep expertise in multi‑agent frameworks such as LangGraph, AutoGen, or CrewAI.
• Proven experience designing or implementing Model Context Protocol (MCP) or similar context‑sharing protocols.
• Strong command of Python, TypeScript, or Go and cloud‑native technologies (AWS/GCP/Azure, Kubernetes, Docker).
• Hands‑on experience with prompt engineering, Retrieval‑Augmented Generation (RAG) pipelines, and vector databases.
• Demonstrated ability to produce high‑quality, production‑ready code and prototypes.
• Outstanding verbal and written communication skills, with a track record of leading technical discussions.
• Experience authoring architecture RFCs and establishing engineering standards.
• Ability to translate complex AI concepts into actionable solutions for business stakeholders.
• Bachelor’s or higher degree in Computer Science, Engineering, or a related field.