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AI Developer

Stevenage
3 weeks ago
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AI Developer

Remote AI / Azure / Python Developer - AI Platform Powering Workflows

Lead Python Software Developer - AI MarTech SaaS- c£90K 4 Day Week

Lead Python Software Developer - AI MarTech SaaS- c£90K 4 Day Week

Lead Python Software Developer - AI MarTech SaaS- c£90K 4 Day Week

Lead Python Software Developer - AI MarTech SaaS- c£90K 4 Day Week

About the Role

We are seeking a highly skilled and experienced Staff AI Developer to lead the design, development, and deployment of production-grade AI systems. This is a hands-on and strategic role where you’ll work with advanced technologies like large language models (LLMs), agentic AI frameworks, graph neural networks (GNNs), and knowledge graphs to build intelligent, autonomous solutions that deliver real business value.

Key Responsibilities

  • Design, pre-train, fine-tune, and evaluate domain-specific LLMs (e.g., GPT, LLaMA, Mistral)

  • Build and orchestrate multi-agent architectures using LangChain, LangGraph, CrewAI, or similar

  • Develop Retrieval-Augmented Generation (RAG) pipelines and apply advanced prompt engineering

  • Implement secure, scalable inference services using REST/gRPC or event-driven APIs

  • Construct and maintain enterprise-scale knowledge graphs and search/recommendation pipelines

  • Develop and optimise GNN models for structured and semi-structured datasets

  • Drive MLOps best practices: CI/CD, model versioning, monitoring, automated retraining and rollback

  • Mentor engineers, conduct code reviews, and shape technical direction and research agendas

    Core Requirements

  • MSc or PhD in Computer Science, Machine Learning, Mathematics, or equivalent industry experience

  • 5+ years of experience in ML/software engineering, with deep knowledge of Python

  • Strong hands-on experience with deep learning frameworks (e.g., PyTorch, TensorFlow, JAX)

  • Proven track record in pre-training or fine-tuning large-scale LLMs

  • Experience deploying AI agents and multi-agent systems in real-world environments

  • Knowledge of GNN libraries (e.g., PyTorch Geometric, DGL) and graph databases (e.g., Neo4j, Neptune)

  • Proficient in building pipelines using Spark, Flink, or Databricks and deploying on AWS, GCP, or Azure with Kubernetes/Terraform

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