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 principles for enterprise AI agents.
• •Address risks including:
• •Prompt injection
• •Data leakage
• •Unauthorised tool usage
• •Excessive agent permissions
• •Inaccurate or unsafe actions
• •Sensitive-data exposure

• •Define appropriate human-in-the-loop controls.
• •Ensure solutions comply with organisational security, privacy, regulatory, and responsible-AI requirements.

AI Evaluation and Observability

• •Define architecture for AI application monitoring and observability.
• •Establish approaches for evaluating agent accuracy, reliability, latency, cost, and task completion.
• •Define appropriate logging, tracing, metrics, and alerting.
• •Establish operational processes for monitoring and continuously improving production agents.

Stakeholder and Technical Leadership

• •Work directly with senior business and technology stakeholders to define AI strategies and roadmaps.
• •Lead architecture workshops and technical design sessions.
• •Communicate complex AI concepts and architectural trade-offs to technical and non-technical audiences.
• •Provide technical direction to AI engineers, developers, data teams, and platform engineers.
• •Review solution designs and ensure alignment with enterprise architecture standards.
• •Mentor engineering teams and promote reusable AI architecture patterns.

Required Experience

• •Significant experience in solution architecture, software architecture, AI architecture, or a related role .
• •Hands-on experience designing and deploying LangGraph-based AI applications or agentic workflows .
• •Strong understanding of LLM application architectures.
• •Experience with enterprise AI/ML solutions in production.
• •Strong understanding of RAG, tool calling, agent orchestration, and human-in-the-loop patterns.
• •Strong experience with at least one major cloud platform: AWS, Azure, or GCP .
• •Strong understanding of enterprise integration patterns and APIs.
• •Experience with security, governance, observability, and operational requirements for production systems.
• •Strong technical understanding of Python and modern software engineering practices.

Desirable Experience

• •LangChain / LangSmith
• •Multi-agent architectures
• •Enterprise RAG platforms
• •Vector databases
• •Kubernetes
• •Event-driven architectures
• •Microservices
• •Infrastructure as Code
• •CI/CD
• •MLOps / LLMOps
• •AI security
• •Responsible AI
• •Large-scale enterprise transformation
• •Experience working directly with senior client stakeholders

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