Senior Artificial Intelligence Engineer

About Scrumconnect Consulting:

Scrumconnect Consulting, a multi-award-winning firm recognized with UKIT awards such as Best Public Sector IT Project, Digital Transformation Project of the Year, and a Special Award for Organisational Excellence during the pandemic, is at the forefront of innovation in tech consulting. Our work impacts over 40 million UK citizens, with successful projects in key government departments like the Department for Work and Pensions, Ministry of Justice, HM Passport Office, and more.
Overview

Were seeking a seasoned Data Lead to own and deliver the data strategy for Govt client that uses services used by over 18m citizens encompassing three newly rebuilt benefits systems. You will define where our data capabilities are today, set the future vision, and architect the roadmap to get us there—then design the data team to execute it.

About the Role

This is a Senior Level, hands-on role for someone who loves building end-to-end AI solutions. You will work closely with the engineering and product teams to develop robust machine learning models and AI-driven features. This role is ideal for candidates who enjoy working in fast-paced environments, taking ownership of technical components, and solving real-world problems with AI.

Responsibilities

AI Development & Integration

• Develop, train, and optimize models in NLP, deep learning, or LLMs
  
• Build full model pipelines: data preprocessing, model training, evaluation, and deployment
  
• Work with tools like PyTorch, TensorFlow, Hugging Face, or JAX
  
• Integrate AI models into production environments with a focus on scalability and performance
  
• Contribute to AI feature prototyping and experimentation
  

AI Infrastructure & Deployment

• Use cloud platforms (AWS, GCP, or Azure) to deploy AI solutions
  
• Utilize Docker and Kubernetes for containerized deployments
  
• Maintain model reliability, version control, and performance monitoring in production
  

Data Engineering & MLOps

• Work on ETL processes and data pipelines to support model development
  
• Follow MLOps best practices for CI/CD, model tracking, and monitoring
  
• Ensure performance, scalability, and maintainability of AI systems
  

Requirements

Minimum Qualifications

• 7+ years of experience in software or AI/ML engineering roles
  
• Proven experience building and deploying ML models, especially in NLP or deep learning
  
• Proficient in Python and familiar with libraries like PyTorch, TensorFlow, or Hugging Face
  
• Experience with cloud services (AWS, GCP, or Azure) and container tools (Docker, Kubernetes)
  
• Good understanding of data structures, algorithms, and distributed systems
  

Preferred Qualifications

• Experience working with large language models (LLMs) such as GPT, BERT, etc.
  
• Exposure to MLOps tools (e.g., MLflow, Weights & Biases, Kubeflow)
  
• Background in legal-tech or regulated domains (a plus, not required)
  
• Experience working in fast-paced startup environments or early-stage product development