Solutions Architect – Agentic AI

Our client is seeking a Solutions Architect to take ownership of the end-to-end technical architecture for large-scale, multi-agentic AI platforms. This is a hands-on, build-first role where you will design agent orchestration systems, write production code, and lead a technical team while remaining closely involved in implementation. This position is not focused on pre-sales or solutioning only.

Key Responsibilities:

• Design end-to-end multi-agentic architectures including orchestration, inter-agent communication, memory, tool/function-calling, and human-in-the-loop workflows.
• Build foundational agents and reusable templates; set the code quality bar through your own commits and PR reviews.
• Architect secure integrations with CRMs (e.g., Salesforce), ERPs, ITSM tools, and line-of-business systems via APIs, events, and MCP-based tool servers.
• Own scalability, security, and reliability aspects such as multi-tenancy, LLM guardrails, prompt-injection defenses, PII handling, observability, and agent evaluation.
• Ensure architectures comply with applicable data residency, privacy, and information security requirements.
• Lead a pod of AI engineers; define coding standards, design patterns, and release governance while mentoring team members.
• Represent technical solutions to client CXOs and IT teams; translate business problems into agent capabilities.
• Collaborate with delivery leadership on estimation, phasing, and technical risk management.

Required Qualifications:

• 8-12 years of hands-on software engineering experience, with a solid technical track record, including roles in architecture.
• Experience architecting and shipping at least one enterprise-grade multi-agent system in production, not just a proof of concept, with real users and measurable outcomes.
• 3+ years of experience with LLM/GenAI systems, including RAG pipelines, prompt engineering, structured outputs, and tool calling across providers.
• Hands-on expertise in a major agent framework (e.g., LangGraph, CrewAI, AutoGen, OpenAI Agents SDK, Bedrock Agents/Strands, or Semantic Kernel).
• Strong understanding of multi-agent orchestration patterns, agent-to-agent communication, and memory/state design.
• Experience with Model Context Protocol (MCP) and tool-use architecture, including permissioning and sandboxing.
• Strong Python skills (TypeScript/Node.js is a plus) with production-grade testing, CI/CD, and API design practices.
• Experience with cloud-native architecture on AWS and/or Azure, including containers, serverless, event backbones, IaC, and vector databases.
• Strong enterprise-grade architecture judgment on scalability, availability, security, and vulnerability management (e.g., OWASP Top 10 / LLM Top 10, zero-trust, DR/BCP).
• Experience integrating enterprise systems such as Salesforce, Microsoft Dynamics, ServiceNow, or SAP.

Preferred Qualifications:

• Experience working with stakeholders from the Middle East, ideally government or semi-government entities.
• Experience with multilingual conversational or agentic AI experiences (e.g., Arabic/English).
• Relevant certifications such as AWS Solutions Architect Professional, AWS ML Specialty, or Azure Solutions Architect Expert.
• Experience with fine-tuning, model distillation, or self-hosted/open-weight model deployment.
• Contributions to open-source projects, technical writing, or conference speaking in the AI/agentic space.

What We Offer:

• Ownership: you will have full authority over the architecture and technical decisions.
• AWS Advanced Tier ecosystem: direct access to AWS specialist teams and competency pathways.
• Global exposure: work with clients across 20+ countries and engage regularly with senior leadership.
• Career trajectory: a credible path to Principal Architect or Head of AI Engineering.