AI Solutions Engineer

One Zero Digital Bank is looking for a hands-on AI Solutions Engineer to accelerate practical, governed AI adoption across the bank’s business functions. 

This role is for a builder with strong product instincts: someone who can sit with Operations, Legal, GRC, Compliance, Finance, Risk, Advisory, and other non-R&D teams, understand how work actually happens, identify high-value manual workflows, and turn them into secure AI-powered solutions. 

You will design, build, pilot, and scale internal AI tools, agent-powered workflows, copilots, automations, and business-facing AI applications using platforms such as AWS Bedrock, Google Vertex AI, Gemini Enterprise, Azure OpenAI, Claude Code, workflow automation tools, and similar technologies. 

This is not a strategy-only role. It is also not a pure engineering role. It is a hands-on, forward-deployed builder role at the intersection of Product, Engineering, Operations, and Enterprise AI Transformation. 

• Partner directly with non-R&D teams to understand workflows, pain points, decision processes, manual tasks, and operational bottlenecks. 
• Identify and prioritize AI and automation opportunities based on business impact, feasibility, adoption potential, data readiness, cost, security, risk, compliance, and control requirements. 
• Translate ambiguous business problems into clear AI use cases, MVP definitions, solution designs, success metrics, and rollout plans. 
• Build and configure AI-powered solutions, including internal copilots, agentic workflows, workflow automations, RAG-based tools, document-processing flows, decision-support tools, and integrations with internal systems. 
• Prototype quickly, validate with users, and iterate based on real workflow feedback. 
• Work with Engineering, Data, Security, Legal, Risk, and Compliance teams to ensure solutions are safe, governed, auditable, and aligned with bank standards. 
• Lead pilots and production rollouts, including training, enablement, documentation, and adoption support. 
• Track usage, reliability, quality, cost, productivity gains, and business outcomes after launch. 

•  5+ years in a technical role such as software engineering, solutions engineering, technical product management, automation engineering, data/AI engineering, or a similar hands-on role. 
• 1+ years of practical experience delivering AI, GenAI, agentic, or automation solutions for business or operational users. 
• A clear builder track record: you have shipped tools, automations, workflows, internal products, or prototypes that people actually used. 
• Hands-on experience with AI platforms, coding agents, LLM APIs, agent frameworks, workflow automation tools, low-code/no-code platforms, or enterprise AI products. 
• Practical understanding of LLMs, RAG, prompt design, AI agents, tool use, human-in-the-loop workflows, evaluations, and responsible AI patterns. 
• Product judgment: ability to prioritize, define MVPs, separate nice-to-have ideas from high-value use cases, and measure outcomes. 
• Strong discovery skills with non-technical stakeholders: you can map how work happens today and redesign it around AI, automation, and human accountability. 
• Excellent communication skills: able to explain technical tradeoffs to business stakeholders and business context to technical teams. 
• Strong ownership and execution: comfortable moving from ambiguous problem to working solution. 
• Experience in a regulated environment such as banking, fintech, insurance, payments, healthcare, or another high-control industry is a strong advantage.