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Agentic & MCP Architect (Principal / Expert)
About the Project / Role Context:
For our client – an international FinTech & Telecom group – we are building a world-class AI capability (AI Squad) from the ground up. We create autonomous and semi-autonomous agentic systems and intelligent platforms that will transform and automate financial services for millions of users.
We are seeking an Agentic & MCP Architect to serve as the chief Design Authority for agentic systems across Group FinTech. This is a hands-on architecture role within a build team – ranging from designing agent frameworks and tool servers, through defining context protocols (MCP) and integration patterns, to ensuring predictable, safe execution in production environments.
Key Responsibilities:
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Agentic Architecture: Design advanced agentic systems, including planning, memory structures, orchestration mechanisms, and multi-agent design patterns.
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Tool & Context Integration Layer: Design and build Model Context Protocol (MCP) servers and connectors, enabling agents to interact safely with enterprise systems.
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Execution Patterns & Runtime: Develop reusable execution patterns, agent templates, and the agent runtime environment.
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Safe Action Design: Design permissioning frameworks, human-in-the-loop oversight, escalation mechanisms, and automated rollbacks for agent-initiated actions.
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Evaluation & Quality: Design agent evaluation frameworks and monitor behavioral quality and safety in production.
Requirements (Must-have):
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Experience: Minimum 8–10 years of experience in software or machine learning engineering, including at least 3 years in a Technical Design Authority or Lead Engineering role.
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Production Agentic Practice: Proven hands-on track record of designing and deploying agentic or workflow automation systems running at scale in production.
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Domain Expertise: Deep practical knowledge of large language models (LLMs), agent frameworks, tool/function calling, context protocols (MCP), planning, and memory design.
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Enterprise Integration: Experience integrating automated AI systems with core transactional platforms and enterprise applications.
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Guardrails & Security: Experience designing permissioning, guardrails, and human oversight for systems taking action in regulated environments.
Nice-to-have:
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Experience in FinTech, banking, or other high-volume transactional environments.
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Recognized cloud, security, or AI engineering certifications.
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Postgraduate qualification (Master's or Ph.D.) in a technical discipline (Computer Science, Data Science, Mathematics, or a related field).