AI Architect
Neurons Lab
Wymagania
- LLM
Opis stanowiska
About the project You'll be joining Neurons Lab as a Senior AI Solutions Architect, working directly with our Head of AI Engineering to scale our FSI-only AI consultancy. This role is critical for supporting our existing client relationships while building technical capacity for our custom LLM solutions and AI-powered business process transformation projects. Objective - Support business development through technical expertise and client communication - Enable engineering team growth and high-performance delivery - Contribute to critical AI system architecture and implementation KPI - Achieve 90%+ Customer Satisfaction Index (CSI) on technical delivery - Support team performance improvement and capability development - Deliver scalable AI system architectures that meet FSI compliance requirements Areas of Responsibility Business Development Support - Communicate project progress with customers, explaining business and technology logic clearly - Prepare upsell and account expansion ideas for existing clients - Assist in proposal preparation for new client engagements Engineering Team Enablement - Lead AI Engineers on customer projects, create tasks, control performance and share feedback - Help engineering team grow, identify and support high-performers - Participate in performance reviews and performance improvement plans Technical Architecture & Implementation - Take part in critical software pieces implementation - Define how AI transforms business processes; design end-to-end AI-powered experiences - Design scalable AI systems architecture; decide on model selection, deployment patterns, and infrastructure requirements - Bridge business stakeholders and technical teams; translate business needs into technical specifications - Design how multiple AI agents/models work together; define agent-to-agent communication protocols - Establish AI development standards, safety protocols, and compliance frameworks - Design systems for AI safety, bias mitigation, and failure modes; implement monitoring and intervention systems