Intermediate AI Engineer

 

 

Intermediate AI Engineer Position Overview

Metrofibre Networks is seeking an Intermediate AI Engineer to join its AI transformation initiative. This role is suited to someone with 3–6 years of experience who is comfortable working across the AI stack while beginning to take ownership of solutions and supporting the development of more junior team members.

You will work alongside the existing AI team, contributing to the design, development, and productionisation of AI solutions, while helping to stabilise and mature engineering practices. This role offers the opportunity to deepen specialisation in key areas (e.g., ML engineering, data engineering, or AI infrastructure) while playing a hands-on and influential role within the team.

 

KEY RESPONSIBILITIES

AI Solution Development & Deployment

• Design, build, and deploy machine learning and AI-driven solutions across use cases (NLP, time series, and generative AI)

• Work with LLMs, including prompt engineering, RAG architectures, and agent-based workflows

• Develop production-grade APIs and microservices to serve AI models • Contribute to model optimisation, evaluation, and continuous improvement

Data Engineering & Pipelines

• Build and maintain scalable data pipelines (ETL/ELT) for AI workloads • Work with structured and unstructured data across SQL, NoSQL, and vector databases • Ensure high data quality and readiness for downstream ML use cases • Support real-time and batch data processing workflows

 

 

 

AI Operations & Infrastructure

• Deploy, monitor, and maintain ML models in production environments • Contribute to MLOps practices, including CI/CD pipelines and model lifecycle management • Use containerisation (Docker) and orchestration tools (Kubernetes) • Monitor model performance, identify drift, and support retraining processes

Platform & System Contribution

• Contribute to the development of internal AI platforms and reusable tooling • Support infrastructure-as-code practices and scalable architecture design • Work within microservices-based environments and API-driven systems

Team Collaboration & Mentorship

• Collaborate with product, data, and engineering stakeholders to translate business problems into AI solutions

• Provide support and guidance to junior engineers and graduates within the team • Participate in code reviews and promote engineering best practices • Take ownership of specific components or features

Continuous Improvement

• Stay up to date with developments in AI/ML and recommend practical applications • Contribute to improving processes, tooling, and delivery standards within the team

 

REQUIRED QUALIFICATIONS

Education

• Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field

Experience

• 3–6 years of hands-on experience in software engineering, data engineering, or AI/ML

Technical Skills

• Strong programming experience in Python (essential) • Solid understanding of machine learning fundamentals and model lifecycle • Experience with ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn) • Strong SQL and data handling skills • Experience with API development and system integration • Familiarity with cloud platforms (AWS, Azure, or GCP)

 

 

• Exposure to Docker, Kubernetes, and CI/CD pipelines • Understanding of software development best practices and design patterns

 

Advantageous Skills

• Experience with LLMs, generative AI, and prompt engineering • Exposure to RAG architectures and vector databases • Experience with MLOps tooling (MLflow, Weights & Biases, etc.) • Familiarity with data pipeline/orchestration tools (Airflow, Prefect, etc.) • Understanding of data governance and AI ethics principles • Experience working in production AI or high-scale environments

 

Key Attributes

• Strong problem-solving and analytical thinking skills • Ability to operate independently while contributing to a team environment • Comfortable taking ownership and driving delivery • Strong communication skills across technical and business stakeholders • Interest in mentoring and supporting team growth • Adaptable and comfortable working in an evolving AI landscape

 

WHAT THIS ROLE OFFERS

• Opportunity to play a meaningful role in scaling an AI capability • Exposure across the full AI stack with room to specialise • A collaborative environment with a mix of early-career and experienced engineers • Clear progression path toward senior or specialist roles • Hybrid working model and market-related compensation