Junior AI Engineer - Remote

Attercop; Brighton; Hybrid; GBP 32,000 - 46,000; Full time

Job summary

Attercop is seeking a Graduate AI Engineer to join our Brighton-based engineering team. You’ll work with experienced engineers and data scientists on applied AI projects, focusing on model integration, agentic workflows, data engineering, and early deployment exposure.

You’ll gain hands-on experience in Docker, Azure, and CI/CD while building production AI services, ETL pipelines, and multi-agent components.

Qualifications

• Degree in Computer Science, AI, Software Engineering, Data Science, or similar.
• Strong academic performance.
• Solid Python (NumPy, Pandas, core data structures).
• Understanding of software engineering fundamentals (Git, testing).
• Basic ML knowledge (supervised learning, neural networks, NLP).
• Strong analytical problem-solving.
• Exposure to FastAPI/Flask/Django.
• Cloud familiarity (Azure/AWS/GCP).
• Docker basics.
• Interest in LLMs, prompt engineering, or GenAI.
• Personal projects, hackathons, open-source contributions.
• Experience with async Python or type hinting.

Responsibilities

• Support senior engineers in building production AI services
• Write clean Python for data processing, inference, and APIs
• Contribute to testing, validation, and performance optimisation
• Learn frameworks like LangChain, LangGraph, and Microsoft Agent Framework
• Build components for multi-agent systems
• Apply prompt engineering and RAG techniques
• Contribute to internal research and documentation
• Assist with ETL pipelines and dataset preparation
• Work with PostgreSQL and gain exposure to NoSQL/vector databases
• Support data quality and governance practices
• Learn Docker and containerisation
• Gain hands-on experience with Azure
• Contribute to CI/CD pipelines and basic monitoring

Skills

Python

Data processing

NLP

Analytical thinking

Async Python

Git

Testing

AI fundamentals

Prompt engineering

LLMs

Education

Degree in Computer Science

Tools

Docker

PostgreSQL

NoSQL / Vector DBs

LangChain

LangGraph

Microsoft Agent Framework

Azure

FastAPI/Flask/Django

Job description

Brighton (Hybrid), Europe (Remote), United Kingdom

Full Time

Location: UK (Brighton, Hybrid) / Europe (Remote)

About Attercop

Attercop is a knowledge engineering and agentic AI company built specifically for private equity and professional services. We turn fragmented, hard to use information into structured intelligence and deploy autonomous AI agents that make decisions, not just recommendations. Our systems deliver faster insights, operational efficiency gains, and real value creation across the PE lifecycle, from diligence and data organisation to portfolio wide transformation.

Role Overview

You’ll join our engineering team as a Graduate AI Engineer, working with experienced engineers and data scientists on applied AI projects. Expect hands-on model integration, agentic workflow development, data engineering fundamentals, and early exposure to deployment and DevOps. This role offers structured progression, mentorship, and real responsibility from day one.

Core Responsibilities

Support senior engineers in building production AI services

Write clean Python for data processing, inference, and APIs

Contribute to testing, validation, and performance optimisation

Agentic Workflows

Learn frameworks like LangChain, LangGraph, and Microsoft Agent Framework

Build components for multi-agent systems

Apply prompt engineering and RAG techniques

Contribute to internal research and documentation

Assist with ETL pipelines and dataset preparation

Work with PostgreSQL and gain exposure to NoSQL/vector databases

Support data quality and governance practices

Deployment & DevOps

Learn Docker and containerisation

Gain hands-on experience with Azure

Contribute to CI/CD pipelines and basic monitoring

What We’re Looking For

Education

Degree in Computer Science, AI, Software Engineering, Data Science, or similar

Strong academic performance

Solid Python (NumPy, Pandas, core data structures)

Understanding of software engineering fundamentals (Git, testing)

Basic ML knowledge (supervised learning, neural networks, NLP)

Strong analytical problem-solving

Exposure to FastAPI/Flask/Django

Cloud familiarity (Azure/AWS/GCP)

Docker basics

Interest in LLMs, prompt engineering, or GenAI

Personal projects, hackathons, open-source contributions

Experience with async Python or type hinting