System Architect Position Overview
To drive business growth, we seek an expert system architect who combines deep technical expertise with client-facing leadership. This role involves shaping and leading pre-sales engagements, crafting solution visions, and designing robust agentic architectures that address complex challenges across various industries.
Key Responsibilities:
* Pre-Sales & Architecture Leadership:
o Develop solutions to tackle intricate business challenges in regulated sectors.
o Lead pre-sales engagements – workshops, discovery sessions, RFP/RFI responses, business cases and architecture deep-dives.
o Create demonstrators and PoCs that showcase the art of the possible and accelerate buying confidence.
o Translate scope into delivery-ready programmes, ensuring seamless handover to delivery teams.
o Promote best practice and responsible AI, embedding security, privacy, governance, and ethical considerations from day one.
* Delivery & Capability Building:
o Design, prototype, and deliver production-grade agentic architectures.
o Establish integrations with enterprise systems, APIs, and workflows ensuring scalability and resilience.
o Deploy, monitor, and continuously improve AI agents in real-world client environments.
o Mentor consultants and engineers, elevating capability across the region and contributing to global communities of practice.
Essential Skills:
* Demonstrated track record of building and deploying AI agents or agentic architectures in production, not just PoCs.
* Proven ability to lead pre-sales engagements – shaping solution visions, running workshops, responding to RFPs/RFIs, and designing architectures that win client trust.
* Strong grasp of agentic AI frameworks and orchestration patterns.
* Ability to explain and simplify complex AI concepts to both technical teams and senior executives.
* Solid software engineering fundamentals including CI/CD, observability, testing, and scalable system design.
Desirable Skills:
* Experience designing multi-agent systems or autonomous workflows.
* Knowledge of retrieval-augmented generation (RAG) patterns, vector databases, and fine-tuning techniques.
* Hands-on experience with cloud AI platforms and MLOps practices.
* Publications, conference speaking, or open-source contributions in the AI/agent space.
* Ability to mentor and coach teams.