AI Architect

Zensar Technologies Limited is seeking an experienced AI Architect to shape the future of our AI ecosystem. You will define and implement multi‑agent orchestration frameworks, build scalable Model Context Protocol (MCP) services, and drive the architectural vision of our internal AI development platform, ensuring high performance, security, and developer productivity across the organization.
10+ years of software architecture experience, including 3+ years building production‑grade LLM applications.
Deep expertise in multi‑agent frameworks such as LangGraph, AutoGen, or CrewAI.
Hands‑on experience with prompt engineering, Retrieval‑Augmented Generation (RAG) pipelines, and vector databases.
Proven track record designing or implementing Model Context Protocol (MCP) or similar context‑sharing protocols.
Strong programming skills in Python, TypeScript, or Go.
Extensive experience with cloud‑native technologies (AWS/GCP/Azure, Kubernetes, Docker).
Demonstrated ability to create high‑throughput, low‑latency AI platforms.
Excellent verbal and written communication; ability to author comprehensive architecture RFCs.
Leadership experience mentoring engineers and driving cross‑functional technical alignment.
Bachelor’s or higher degree in Computer Science, Engineering, or a related field.
Design and implement multi‑agent orchestration frameworks with autonomous negotiation, task delegation, and secure inter‑agent communication.
Architect, develop, and operate scalable MCP servers and clients that connect LLMs to data sources, tools, and enterprise environments.
Define the technical roadmap for the internal AI development platform, focusing on throughput, latency, and seamless CI/CD pipelines.
Write production‑grade code, create prototypes, and establish engineering best practices for AI application development.
Standardize architectural patterns, guidelines, and reusable components across the organization.
Mentor junior engineers and foster a culture of continuous learning in AI and agentic technologies.
Collaborate with product, data, and security teams to align AI solutions with business objectives and compliance requirements.
Lead technical discussions, produce detailed architecture RFCs, and communicate complex concepts to non‑technical stakeholders.
Evaluate and integrate emerging AI SDKs, vector databases, and cloud‑native services (AWS/GCP/Azure, Kubernetes, Docker).
Monitor system performance, conduct root‑cause analysis, and drive continuous improvement of AI services.

Skills
Python, TypeScript, AWS, Azure, GCP, Docker, Kubernetes, CI/CD, LLM, Negotiation