Senior AI Engineer - Production ML & Agentic AI

WeDoTech; Greater London; Hybrid; GBP 148,000 - 221,000; Full time

Job summary

Agentic AI & Applied ML in London is seeking a Staff ML Engineer to drive production-grade AI/ML systems and adoption of agentic AI across engineering teams. The role focuses on robust architectures, governance and scalable deployment in a hybrid London environment.

You will influence senior engineers, define standards, and enable capable AI/ML solutions to operate safely in production while leveraging LangChain/LangGraph and retrieval frameworks.

Qualifications

• Experience designing robust AI/ML systems for production.
• Strong software engineering fundamentals with Python.
• Production-grade ML deployment and monitoring experience.

Responsibilities

• Design production-grade AI/ML systems with robust architectures.
• Drive adoption of Agentic AI across multiple engineering teams.
• Define reusable engineering standards and implementation patterns.
• Design and evolve production RAG and retrieval architectures.
• Establish LangGraph patterns for agentic apps.
• Improve AI evaluation, testing, observability and production monitoring.
• Develop guardrails and controls for hallucination and model risk.
• Support high-risk AI/ML use cases and complex deployments.
• Establish best practice across MLOps, CI/CD and deployment.
• Influence senior engineers and stakeholders without direct line management.
• Help teams use AI-assisted development tools in workflows.

Skills

Python

Production ML

AWS

Agentic AI

RAG

LangChain/LangGraph

Vector databases

MLOps

AI observability

Model risk controls

PyTorch

TensorFlow

Job description

Agentic AI & Applied ML in London is seeking a Staff ML Engineer to drive production-grade AI/ML systems and adoption of agentic AI across engineering teams. The role focuses on robust architectures, governance and scalable deployment in a hybrid London environment.

You will influence senior engineers, define standards, and enable capable AI/ML solutions to operate safely in production while leveraging LangChain/LangGraph and retrieval frameworks.