AI Architect
About The Position
Zensar Technologies is seeking a hands-on Lead AI Systems Architect to design, build, and scale its next-generation AI ecosystem. The role leads the architecture and implementation of Agent-to-Agent frameworks, Model Context Protocol (MCP) integrations, and a proprietary AI development platform. It is deeply technical and requires writing code and translating AI research into robust, production-grade software while bridging engineering teams and stakeholders through clear communication and cross-functional alignment. The architect will develop multi-agent systems and scalable MCP services, guide the internal AI platform toward high throughput and low latency, and establish engineering standards for AI application development. The role also includes technical leadership, mentoring, collaboration across product, data, and security teams, and ongoing evaluation and improvement of AI services. Zensar describes its work environment as open, creative, and collaborative, with offices designed to encourage communication. It offers a comprehensive benefits package to full-time employees. The company states that applicants must be legally authorized to work with Zensar; visa sponsorship may be available for qualified applicants for certain positions.
Requirements
- 10 or more years of software architecture experience, including at least 3 years building and deploying production-grade LLM applications and AI systems.
- 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 experience with Model Context Protocol (MCP) or designing or implementing similar context-sharing and tool-calling protocols for GenAI.
- Strong programming skills in Python, TypeScript, or Go.
- Extensive experience with cloud-native technologies, including AWS, GCP, or Azure, Kubernetes, and Docker.
- Demonstrated ability to create high-throughput, low-latency AI platforms.
- Excellent verbal and written communication skills and ability to author comprehensive architecture RFCs.
- Leadership experience mentoring engineers and driving cross-functional technical alignment.
- College or university degree or higher; the qualifications section specifies a bachelor's degree or higher in Computer Science, Engineering, or a related field.
- Must be legally authorized to work with Zensar.
Responsibilities
- Design and implement multi-agent orchestration frameworks supporting autonomous negotiation, task delegation, state management, and secure inter-agent communication.
- Architect, develop, and operate scalable MCP servers and clients that connect LLMs to data sources, development tools, and enterprise environments.
- Define the technical roadmap and architecture for the internal AI development platform, focusing on throughput, latency, and seamless developer workflows and 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 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 explain complex concepts to non-technical stakeholders.
- Evaluate and integrate emerging AI SDKs, vector databases, and cloud-native services.
- Monitor system performance, conduct root-cause analysis, and drive continuous improvement of AI services.
Benefits
- Comprehensive benefits package for full-time employees.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
