AI Architect

Zensar; San Jose (CA); On-site; USD 210,000 - 320,000; Full time

Job summary

Zensar is seeking a highly skilled Lead AI Systems Architect in San Jose to design, build, and scale our next-generation AI ecosystem. You will lead architecture and implementation of Agent-to-Agent frameworks, MCP integrations, and our internal AI development platform, translating research into production-grade software.

This hands-on role requires deep technical能力, coding, and strong communication to align engineering with business goals.

Qualifications

• 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 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

Responsibilities

• 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

Architectural design

Leadership

Communication

Mentoring

RFC writing

Education

Bachelor’s or higher in CS/Engineering

Tools

LangGraph

AutoGen

CrewAI

MCP (Model Context Protocol)

Python

TypeScript

Go

AWS

GCP

Azure

Kubernetes

Docker

Job description

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.

Zensar values your privacy. We’ll use your data in accordance with our privacy statement located at: https://zensar.com/privacy-notice

• 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.

At Zensar, we’re

“experience-led everything”

We are committed to conceptualizing, designing, engineering, marketing, and managing digital solutions and experiences for over 130 leading enterprises.

We are a company driven by a bold purpose:

Together, we shape experiences for better futures

Whether for our clients, our people, or the world around us, this belief powers everything we do.

At the heart of our culture is

ONE with Client - a set of four core values that reflect who we are and how we work:

One Zensar, Nurturing, Empowering, and Client Focus.

Part of the $4.8 billion RPG Group, we’re a community of 10,000+ innovators across 30+ global locations, including Milpitas, Seattle, Princeton, Cape Town, London, Zurich, Singapore, and Mexico City.

Explore Life at Zensar and join us to Grow. Own. Achieve. Learn. to be the best version of yourself.

We believe the best work happens when individuality is celebrated, growth is encouraged, and well-being is prioritized.

We are an equal employment opportunity (EEO) and affirmative action employer, committed to creating an inclusive workplace. All qualified applicants will be considered without regard to race, creed, color, ancestry, religion, sex, national origin, citizenship, age, sexual orientation, gender identity, disability, marital status, family medical leave status, or protected veteran status.