Senior AI Engineer - LLM Systems & Production

Meltwater Group; City Of London; Hybrid; GBP 90,000 - 130,000; Full time

Benefits offered by this job

Flexible PTO

Health insurance

Calm App

Hybrid work

Family leave

Professional development

Job summary

Meltwater is seeking an AI Engineer with 5+ years of hands-on experience to design, build, and deploy AI-powered solutions. You will focus on LLM-powered applications, data enrichments, multi-agent workflows, and autonomous AI systems that impact user experiences.

You will own end-to-end delivery from concept through production, containerizing services, building deployment pipelines, and establishing monitoring for performance, reliability, and AI-specific metrics like hallucinations and

Qualifications

• 5+ years hands-on AI/ML engineering and related roles with demonstrable AI deployments
• Theoretical knowledge of AI/ML/NLP with CS degree or equivalent
• Python proficiency; familiarity with Java/Kotlin; API design & integration patterns

Responsibilities

• Own end-to-end AI solution delivery from concept to production deployment
• Architect and implement LLM-powered apps, enrichments, multi-agent workflows and autonomous AI systems
• Containerize services, build deployment pipelines, and monitor performance, hallucination rates, and decision accuracy
• Manage infrastructure for AI apps with automated evaluation, security, and rapid iteration

Skills

AI/ML engineering

Software development

Python

Java/Kotlin

Prompt engineering

LLM orchestration

Cloud platforms

Docker

Kubernetes

CI/CD

Education

Bachelor's or master's in CS or equivalent

Tools

LangChain

LangGraph

OpenAI API

Anthropic API

Docker

Kubernetes

Azure Cloud

AWS

Google Cloud

Job description

Meltwater is seeking an AI Engineer with 5+ years of hands-on experience to design, build, and deploy AI-powered solutions. You will focus on LLM-powered applications, data enrichments, multi-agent workflows, and autonomous AI systems that impact user experiences.

You will own end-to-end delivery from concept through production, containerizing services, building deployment pipelines, and establishing monitoring for performance, reliability, and AI-specific metrics like hallucinations and