Senior Applied AI Engineer - On-Site Hybrid, SC/DV Eligible

Oxford Dynamics; Greater London; Hybrid; GBP 129,000 - 166,000; Full time

Benefits offered by this job

Hybrid working pattern

Job summary

Oxford Dynamics is seeking a Senior Applied AI Engineer to build end-to-end agentic AI systems for high-stakes environments, with a focus on reliability, security, and production readiness. The role involves owning pipelines from data ingestion to inference, and delivering robust solutions on hybrid on-site/remote arrangements in Oxford or London.

The successful candidate will have 6+ years of software engineering, strong Python skills, and hands-on experience with multi-agent AI systems and LLM

Qualifications

• Significant professional software engineering experience (typically 6+ years) with senior/lead background.
• Strong Python expertise and hands-on experience with LLM frameworks (LangGraph, LangChain, Haystack, or similar).
• Commercial experience building multi-agent or agentic AI systems in production, owning them as an engineer.

Responsibilities

• Build agentic AI systems in production: design multi-agent pipelines, reasoning and retrieval, model integration and deployment infrastructure.
• Own features end-to-end and be accountable for behavior under pressure, including security and reliability constraints.
• Set technical bar as a technical authority, guiding design patterns and knowledge transfer.

Skills

Senior software engineering

Python

LLM frameworks

Multi-agent AI

Production-grade code

Tools

LangGraph

LangChain

Haystack

Job description

Oxford Dynamics is seeking a Senior Applied AI Engineer to build end-to-end agentic AI systems for high-stakes environments, with a focus on reliability, security, and production readiness. The role involves owning pipelines from data ingestion to inference, and delivering robust solutions on hybrid on-site/remote arrangements in Oxford or London.

The successful candidate will have 6+ years of software engineering, strong Python skills, and hands-on experience with multi-agent AI systems and LLM