Senior AI Engineer

Gradient Labs is building an AI customer operations platform for financial services. The Senior AI Engineer will build, evaluate, operate, and improve production AI agents, translating ambiguous customer support problems into reliable agentic workflows and contributing to the company’s internal AI platform.

Responsibilities:

• Build and operate AI agents in production: Design, implement, and maintain agentic systems powered by LLMs - handling tool calling, multi-step reasoning, and integration with customer APIs and data sources. You'll own these systems end-to-end: reliable, observable, and auditable from day one
• Translate business problems into agentic workflows: Take on ambiguous, open-ended problems (like "help our agent handle conversations in multiple languages") and turn them into scoped, shippable projects
• Strong product mindset: Prioritise product thinking over pure ML technique, optimising for customer and business value rather than model performance for its own sake
• Build robust evaluation infrastructure: Create and maintain eval suites drawn from real-world scenarios and edge cases. Go beyond vibes-based testing: structured evals measuring accuracy, safety, and latency, tied to clear business outcomes, used to drive systematic improvements to prompts, tools, and behaviour
• Enhance our agent: Develop, evaluate, and optimise the skills that make up our agent. Curate datasets, iterate on improvements, test changes, and ship successful approaches into production
• Shape our internal AI platform: Contribute to shared libraries, patterns, and standards for how we build, evaluate, and deploy agents across customers. Help define how we approach prompting, tool orchestration, retrieval, and monitoring
• Experiment and prototype: Keep up with the latest in NLP, agentic systems, and generative AI. Prototype against our hardest problems with a bias toward shipping experiments quickly rather than long research cycles. Our agents already handle tens of thousands of real customer conversations every hour, so your work has immediate, visible impact
• Analyse data: Work across customer queries, support tickets, and related data to find patterns and identify what our agents could automate next
• Drive technical decisions: Scope your own work, push back when the framing is wrong, and tell us when the plan needs to change