AI Solutions Architect

Neurons Lab is an FSI-focused AI consultancy that embeds directly with enterprise clients — banks, insurers, and financial institutions — to design and deliver AI transformation. As an AI Solutions Architect in our Talent Network, you will be the technical lead on client engagements, designing and delivering production-ready AI architectures. Most projects enter the discovery or pilot stage and run 6–12 weeks. This is a Talent Network engagement, not a full-time position. Projects are scoped and initiated by Neurons Lab when a client engagement begins. You are invited to join when a matching project is available, and you are free to take it. You work as a freelance contractor at 0.25–0.5 FTE per project (10–20 hrs/week). Between projects, there may be gaps, and you're free to hold other commitments alongside Neurons Lab. 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 (not all projects require AI Engineers) - Help the engineering team grow, identify, and support high-performers - Participate in performance reviews and performance improvement plans Technical Architecture & Implementation - Take part in the implementation of critical software pieces - 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