AI Engineer: Agentic Systems in Secure Environments

Oho Group; Greater London; Hybrid; GBP 90,000 - 130,000; Full time

Benefits offered by this job

Competitive salary and equity

Private healthcare

Relocation support

Relocation assistance

Job summary

Oho Group in London is seeking an AI Engineer with strong software engineering fundamentals to help build agentic systems for secure, mission-critical environments. This role focuses on architecting production services, integrating models, and ensuring reliability across the stack.

You will work across architectures, agent orchestration, tool use and model context protocols, evaluating LLMs and traditional software to deliver robust, observable systems.

Qualifications

• Strong software engineering fundamentals with production experience.
• Experience building agentic AI systems or LLM-powered applications in production.
• Proficiency in Python, Rust, C++, Java or similar languages.
• Understanding of software architecture and engineering fundamentals.
• Experience with modern ML/AI frameworks and agent orchestration tools.

Responsibilities

• Design and build agentic AI systems for secure, mission-critical environments.
• Architect and implement production services and integrate models into existing systems.
• Evaluate LLMs and conventional software trade-offs to deliver robust, observable solutions.
• Ensure reliability, security and observability across the stack.

Skills

Software engineering

Python

Rust

C++

Java

Agent orchestration

LLM workflows

ML frameworks

System security

MLOps

Education

Bachelors in CS or related

Tools

LangGraph

Google ADK

MCP

Job description

Oho Group in London is seeking an AI Engineer with strong software engineering fundamentals to help build agentic systems for secure, mission-critical environments. This role focuses on architecting production services, integrating models, and ensuring reliability across the stack.

You will work across architectures, agent orchestration, tool use and model context protocols, evaluating LLMs and traditional software to deliver robust, observable systems.