Production AI Engineer: Build Agentic LLM Systems

Gradient Labs; Greater London; Hybrid; GBP 70,000 - 110,000; Full time

Benefits offered by this job

Private medical insurance

Dental insurance

25 days holiday + bank holidays

Team socials and offsites

Flexible working

London office with hybrid schedule

Job summary

Gradient Labs is building an AI-driven customer operations platform for financial services. We want engineers who can ship practical AI solutions that handle live conversations and automate back-office processes.

You will design prompts, orchestration flows, and evaluation suites, and iterate quickly based on real-world feedback. The role emphasizes a strong product mindset, hands-on work with LLMs, and the ability to translate ambiguous business problems into concrete, scalable AI workflows.

Qualifications

• Professional software engineering experience with ML/NLP/AI is required.
• Experience shipping products to real, live customers at scale preferred.
• Strong product mindset: translate problems into deployable solutions quickly.
• Hands-on experience building with LLMs and integrating tools.
• Comfort with ambiguity and clear, proactive communication.

Responsibilities

• Build and operate AI agents in production, with end-to-end ownership from prompts to tool flows.
• Translate business problems into agentic workflows and scoping projects.
• Influence product decisions with a focus on customer and business value.
• Develop evaluation infrastructure to measure accuracy, safety, and latency.
• Iterate on prompts, tools, and agent capabilities to improve performance.

Skills

ML/NLP/Applied AI experience

Product mindset

Strong communication

Ambiguity tolerance

LLM hands-on

Tools

LLM tooling experience

Job description

Gradient Labs is building an AI-driven customer operations platform for financial services. We want engineers who can ship practical AI solutions that handle live conversations and automate back-office processes.

You will design prompts, orchestration flows, and evaluation suites, and iterate quickly based on real-world feedback. The role emphasizes a strong product mindset, hands-on work with LLMs, and the ability to translate ambiguous business problems into concrete, scalable AI workflows.