Artificial Intelligence Engineer

About the Role

We're looking for an AI Engineer who can take ideas from prototype to production — building scalable AI/ML systems and the data architecture behind them. This is a hands-on role combining strong software engineering, applied machine learning, Generative AI and data engineering .

The ideal candidate will be responsible for developing practical AI solutions that support business transformation, automation and improved decision-making across AGMC.

What You'll Do

• Design, build and optimize ML/DL models and LLM-powered applications , including Agentic AI, Generative AI and RAG solutions.
• Build end-to-end AI pipelines covering training, inference, evaluation and monitoring .
• Develop clean, scalable and well-tested backend services and APIs using FastAPI / Flask .
• Design data architecture and manage data storage, primarily using PostgreSQL , including schema design, data modelling and performance optimization.
• Work with large datasets, including data preprocessing, feature engineering and model evaluation.
• Develop and integrate AI solutions into existing business applications and systems.
• Monitor AI/ML models in production and continuously improve accuracy, latency, reliability and scalability .
• Develop proof-of-concepts and take successful AI solutions through to production.
• Collaborate with IT, Digital, Product, Data and business teams to identify and deliver AI use cases.
• Ensure AI solutions follow appropriate security, privacy, governance and responsible AI practices .
• Stay up to date with emerging AI technologies and identify opportunities to apply them within AGMC.

What We're Looking For

• Strong Python skills and solid software engineering fundamentals, including clean code, testing and Git.
• Hands-on experience with PyTorch and/or TensorFlow .
• Practical experience with Agentic AI, Generative AI, LLMs and RAG .
• Experience with LLM frameworks and tooling such as LangChain and/or LlamaIndex .
• Strong data architecture and database skills, particularly PostgreSQL .
• Familiarity with vector databases such as Pinecone, Weaviate or FAISS.
• Experience with cloud platforms such as AWS, Microsoft Azure or Google Cloud Platform .
• Understanding of MLOps and production deployment, including Docker, Kubernetes, CI/CD and MLflow.
• Experience developing and consuming REST APIs .
• Strong analytical and problem-solving skills.
• Clear communicator with the ability to work independently and take ownership of projects from concept through to production.
• Experience working in an Agile / collaborative environment .

Nice to Have

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering or a related field .
• Experience deploying AI applications at scale within an enterprise environment.
• Strong prompt engineering skills and understanding of AI safety and responsible AI.
• Experience with AI agents and multi-agent architectures.
• Exposure to reinforcement learning or multimodal AI .
• Experience working with automotive, retail, mobility or other customer-focused industries would be an advantage.
• Experience taking AI solutions from proof-of-concept to production .

Tools & Technologies

Python · FastAPI / Flask · PyTorch / TensorFlow · PostgreSQL · SQL · LangChain / LlamaIndex · RAG · Vector Databases · Docker · Kubernetes · Git · AWS · Azure · GCP · MLflow · CI/CD