Enterprise Agentic AI Architect | Multi-Agent AI Leader

The Judge Group; Edison (NJ); On-site; USD 155,000 - 200,000; Full time

Job summary

The Judge Group is seeking an experienced Agentic AI Architect to design and deliver next-generation AI solutions in a client-facing consulting role. The position focuses on architecting autonomous, agent-based AI platforms using LLMs, multi-agent systems, RAG, and responsible AI principles across diverse industries.

You will lead architecture efforts, guide engineering teams through POCs and production deployments, and collaborate with clients to translate business requirements into scalable AI

Qualifications

• Bachelor's degree in Computer Science, Engineering, Data Science, or related field.
• Significant experience designing and implementing enterprise AI solutions.
• Strong knowledge of Large Language Models (LLMs), Generative AI, and Agentic AI architectures.
• Experience designing multi-agent systems and AI orchestration frameworks.
• Hands-on experience with Retrieval-Augmented Generation (RAG) and prompt engineering.
• Strong understanding of cloud platforms, APIs, microservices, and enterprise system integration.
• Experience leading technical teams and guiding solution delivery.
• Excellent client-facing, presentation, and communication skills.
• Ability to travel as required.

Responsibilities

• Define end-to-end architecture for enterprise AI solutions incorporating autonomous agents, LLMs, and advanced AI capabilities.
• Design scalable, resilient, and secure AI systems aligned with business objectives.
• Develop architecture blueprints, reference designs, and implementation roadmaps.
• Facilitate client workshops to understand business challenges and identify opportunities for Agentic AI solutions.
• Translate business requirements into practical and scalable AI architectures.
• Present recommendations, solution designs, and technical strategies to executive and technical stakeholders.
• Design and orchestrate multi-agent AI frameworks where multiple autonomous agents collaborate to solve complex business problems.
• Define agent roles, communication patterns, workflows, governance models, and fail-safe mechanisms.
• Ensure solutions support adaptability, continuous learning, and operational efficiency.
• Provide architectural leadership throughout solution development and deployment.
• Guide engineering teams during proof-of-concepts, prototypes, and production implementations.
• Troubleshoot complex architectural and integration challenges.
• Architect solutions leveraging advanced prompt engineering techniques.
• Design Retrieval-Augmented Generation (RAG) frameworks to enhance accuracy and reliability of AI outputs.
• Establish best practices for knowledge retrieval, grounding, and AI response quality.
• Design integrations with existing enterprise applications, data platforms, APIs, and cloud environments.
• Ensure scalability, performance, security, and maintainability across AI ecosystems.
• Evaluate emerging AI technologies, frameworks, and methodologies.
• Contribute to architecture standards, best practices, and innovation initiatives.
• Serve as a trusted advisor on AI transformation and modernization efforts.
• Incorporate ethical AI principles, governance, risk management, and safety controls into solution designs.
• Identify and mitigate risks related to AI deployment and operationalization.

Skills

LLMs

Generative AI

Agentic AI

Multi-agent systems

RAG & Prompt engineering

Cloud platforms & APIs

Team leadership

Client-facing communication

Willing to travel

Education

Bachelor's degree in CS/Engineering/Data Science

Advanced degree preferred

Tools

Cloud platforms

APIs

Microservices

Job description

The Judge Group is seeking an experienced Agentic AI Architect to design and deliver next-generation AI solutions in a client-facing consulting role. The position focuses on architecting autonomous, agent-based AI platforms using LLMs, multi-agent systems, RAG, and responsible AI principles across diverse industries.

You will lead architecture efforts, guide engineering teams through POCs and production deployments, and collaborate with clients to translate business requirements into scalable AI