AI Systems Architect

Job requirements

• Significant experience designing AI systems inclusive of optical networks and fabrics
• Strong understanding of machine learning, deep learning and modern AI infrastructure.
• Experience with Large Language Models (LLMs), Generative AI and inference optimisation.
• Experience designing scalable cloud or high-performance computing architectures.
• Strong understanding of GPU computing, AI accelerators or advanced compute platforms.
• Experience working with enterprise customers and technical stakeholders.
• Excellent communication and presentation skills.
• Ability to simplify complex technical concepts for a range of audiences.
• Experience working collaboratively across Product, Engineering and Commercial teams.
• Experience with photonic computing, optical systems or semiconductor technologies.
• Knowledge of confidential computing, encryption or secure AI.
• Experience with NVIDIA CUDA, TensorRT or AI acceleration frameworks.
• Experience with Kubernetes, Docker and containerised AI deployments.
• Familiarity with AWS, Azure or Google Cloud AI platforms.
• Experience with PyTorch, TensorFlow or JAX.
• Understanding of distributed AI training and inference.
• Experience within research organisations, national laboratories or defence programmes.
• Experience working within a start-up or scale-up environment.
• Passionate about emerging AI technologies.
• Naturally curious and motivated by solving complex technical challenges.
• Comfortable working across multiple disciplines and teams.
• Customer-focused with excellent relationship-building skills.
• Able to balance technical excellence with commercial awareness.
• A strong communicator who enjoys explaining complex ideas.
• Adaptable and comfortable operating in a fast-moving deep-tech environment.
• Self-motivated, collaborative and proactive.
• Designed scalable AI architectures for key customer deployments.
• Successfully supported enterprise customer evaluations and proof-of-concept projects.
• Become a trusted technical advisor to customers and partners.
• Influenced product development through customer feedback and technical insight.
• Helped establish best practices for deploying Optalysys technology within AI environments.
• Represented Optalysys as a recognised technical expert across the North American market.

Job responsibilities

• Design AI system architectures that leverage Optalysys technology to solve complex computational challenges.
• Develop reference architectures and deployment models for scalable AI environments.
• Support customers in integrating Optalysys solutions into existing AI, HPC and cloud infrastructures.
• Evaluate customer workloads and recommend optimal deployment approaches.
• Act as the primary technical advisor during customer engagements
• Understand customer objectives and translate business requirements into technical solutions.
• Deliver technical presentations, demonstrations and architecture workshops.
• Support proof-of-concept projects and technical evaluations.
• Build trusted relationships with customer engineering, AI and infrastructure teams.
• Work closely with Engineering and Product teams to communicate customer requirements and market feedback.
• Influence future product capabilities through customer insights.
• Support product roadmap discussions with technical expertise.
• Collaborate on technical documentation and implementation best practices.
• Analyse AI workloads to identify performance optimisation opportunities.
• Evaluate large language models, inference pipelines and machine learning workflows.
• Benchmark system performance and identify areas where photonic acceleration provides measurable benefit.
• Develop best practices for deploying AI workloads on Optalysys platforms.
• Provide technical leadership across customer projects.
• Mentor internal teams on AI architectures and emerging technologies.
• Contribute to internal technical strategy and architecture standards.
• Support cross-functional teams throughout the customer lifecycle.
• Represent Optalysys at technical conferences, industry events and customer workshops.
• Publish technical content, whitepapers and architecture guidance where appropriate.
• Build relationships within the AI, semiconductor and photonics communities.
• Stay informed on emerging AI technologies, frameworks and industry trends.

Job benefits