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AI Architect

Job in Durham, Durham County, North Carolina, 27701, USA
Listing for: Zensar Technologies
Full Time, Part Time position
Listed on 2026-11-01
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), Software Architect
Salary/Wage Range or Industry Benchmark: 150000 - 230000 USD Yearly USD 150000.00 230000.00 YEAR
Job Description & How to Apply Below

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.

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.

Zensar is seeking an AI Architect Role-RTP, North Carolina -(3 days/week onsite).This is open for Full time with excellent benefits and Contract Role as well with outstanding growth opportunities.

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., Lang Graph, Auto Gen, 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, Type Script, 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

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