AI Architect

About Zensar Technologies

Zensar is a leading digital solutions and technology services company partnering with global organizations on their digital transformation journey. A technology partner of choice, with strong track-record of innovation, credible investment in digital solutions and assertion of commitment to client’s success, Zensar’s comprehensive range of services and solutions enable clients achieve new thresholds of performance. Part of the $40 billion APAX Partners’ portfolio of companies, Zensar is uniquely positioned to help existing businesses run efficiently, manage legacy transformation and plan business growth through innovative digital platform. https://www.zensar.com

Working at Zensar

Working at Zensar is an enriching experience. While work is driven by innovation and passion, fun is taken seriously too. An open environment is encouraged making it easy to brainstorm with colleagues. Creative thinking is encouraged through time out activities. Moreover, the offices have been designed to foster creativity and communication, bringing a little bit of home into work every day. Zensar provides and a comprehensive benefit package for all fulltime employees.

Role Overview:

We are seeking a highly skilled, hands-on Lead AI Systems Architect to design, build, and scale our next-generation AI ecosystem. In this role, you will lead the architecture and implementation of Agent-to-Agent frameworks, Model Context Protocol (MCP) integrations, and our proprietary AI development platform.

This is not a purely theoretical role. You must be deeply technical, actively writing code, and capable of translating complex AI research into robust, production-grade software. As a key bridge between engineering teams and stakeholders, you must also possess exceptional communication skills to articulate technical vision and drive cross-functional alignment.

Core Responsibilities:

• Agent-to-Agent Architecture: Design and implement multi-agent orchestration frameworks, focusing on autonomous negotiation, task delegation, state management, and secure inter-agent communication.
• MCP Integration: Architect and build scalable Model Context Protocol (MCP) servers and clients to securely connect LLMs to data sources, development tools, and enterprise environments.
• AI Platform Development: Drive the architectural vision for our internal AI development platform, ensuring high throughput, low latency, and seamless developer workflows for training, testing, and deploying models.
• Hands-on Engineering: Write high-quality, production-ready code, build prototypes, and establish engineering best practices for AI application development.
• Technical Leadership & Communication: Standardize architectural patterns across the organization. Mentor junior engineers and explain complex technical concepts to non-technical stakeholders clearly and effectively.

Required Qualifications & Skills

• Experience: 10+ years of software architecture experience, with at least 3+ years of dedicated, hands-on experience building and deploying production-grade LLM applications and AI systems.
• AI & Agentic Expertise: Deep understanding of multi-agent frameworks (e.g., LangGraph, AutoGen, CrewAI), prompt engineering, RAG pipelines, and vector databases.
• Protocol & API Mastery: Proven experience with Model Context Protocol (MCP) or designing similar context-sharing and tool-calling protocols for GenAI.
• Technical Stack: Proficiency in Python, TypeScript, or Go, along with cloud native technologies (AWS/GCP/Azure, Kubernetes, Docker) and modern AI SDKs.

• Communication: Outstanding verbal and written communication skills, with a proven ability to lead technical discussions and author comprehensive architecture RFCs.

• Education: College/University degree or higher

All applicants must be legally authorized to work with Zensar. Visa sponsorship may be available for qualified applicants for certain positions.

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• 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.

• 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.