Solution Architect - LangGraph & Agentic AI

We are looking for an experienced Solution Architect with hands-on experience designing and deploying LangGraph-based AI solutions to lead the architecture of enterprise agentic AI platforms and applications.

You will work with business and technology stakeholders to identify high-value AI opportunities and translate them into secure, scalable, and production-ready architectures.

The role combines AI architecture, enterprise integration, cloud engineering, agentic AI, security, governance, and stakeholder leadership.

You will be expected to understand LangGraph at a practical level and be able to challenge architectural decisions, guide engineering teams, and ensure that AI solutions can operate reliably at enterprise scale.

Requirements

AI Solution Architecture

• Lead the architecture and design of enterprise AI agent and agentic workflow solutions.
• Design LangGraph-based architectures for single-agent and multi-agent applications.
• Translate business requirements, processes, SLAs, security requirements, and technical constraints into solution architectures.
• Evaluate architectural alternatives and document key technical decisions and trade-offs.
• Define reusable architecture patterns for agentic AI solutions.

Enterprise Agent Architecture

• Design architectures incorporating:
• LLMs
• LangGraph
• RAG
• Enterprise data
• APIs and business systems
• Workflow engines
• Human approval processes
• Observability
• Security and governance
• Define appropriate boundaries between AI reasoning and deterministic business logic.
• Design state management, persistence, recovery, and long-running agent workflows.
• Determine when to use single-agent, multi-agent, or conventional application architectures.

Cloud and Platform Architecture

• Design scalable AI application architectures on AWS, Azure, or GCP.
• Define compute, networking, storage, API, security, and platform requirements.
• Design architectures suitable for enterprise-scale production workloads.
• Evaluate cloud services and AI platform capabilities based on performance, security, scalability, and cost.
• Work with platform engineering and DevOps teams to establish deployment standards.

Integration Architecture

• Design integration between AI agents and enterprise applications, APIs, databases, and SaaS platforms.
• Define secure mechanisms for agent tool access and business-system interactions.
• Design authentication, authorisation, secrets management, and access-control approaches.
• Ensure AI-driven actions are traceable, auditable, and appropriately governed.

AI Security and Governance

• Establish security and governance pri