AI Data Engineer

About DeARX

The idea started in 2001 when a company with a need connected with a few IT experts in search of a solution. Working together, a solution was created and DeARX celebrated with their first customer. At its most basic level, the same is true today, only we have more customers and many more technologists solving more and more problems by building better and better solutions. The technologies have changed, for the better; we've employed amazing people, some of whom have stayed and some who have moved on; our focus remains, to build technology solutions for companies so they become our customers. DeARX has evolved and will continue to do so but core to our business is to value our people, deliver great solutions to our customers, bring the best technology possible to the solution, love what we do and create a legacy that benefits many others now and into the future.

We are seeking a highly skilled AI Data Engineer to design, build, and optimise scalable data and AI solutions within a leading banking environment. The ideal candidate will have deep expertise in modern data engineering practices combined with hands-on experience in LLM orchestration frameworks such as LangChain and LangGraph at an enterprise level. This role will play a critical part in enabling AI-driven decision-making, automation, and advanced analytics across the organisation.

Key Responsibilities

• Design, develop, and maintain scalable data pipelines and architectures to support AI and machine learning initiatives
• Build and optimise LLM-powered applications using Frameworks like LangChain and LangGraph amoungs others
• Develop and manage AI workflows, agents, and orchestration pipelines for enterprise use cases
• Integrate structured and unstructured data sources into AI-ready data platforms
• Collaborate with Data Scientists, ML Engineers, and Business Teams to deliver AI-driven solutions
• Ensure data quality, governance, and compliance within a regulated banking environment
• Optimise performance of data pipelines and AI systems for scalability and reliability
• Implement monitoring, logging, and observability for AI systems and pipelines
• Contribute to data architecture and AI strategy aligned with enterprise roadmaps
• Stay up to date with emerging trends in AI engineering and data platforms

Required Skills & Experience

• 5+ years' experience in Data Engineering or AI Engineering roles
• Strong hands-on experience with LangChain and LangGraph (enterprise-level implementations)
• Proficiency in Python and data engineering frameworks
• Experience building and deploying LLM-based applications and AI agents
• Solid experience with data pipelines (ETL/ELT) and big data technologies
• Experience with cloud platforms (AWS, Azure, or GCP)
• Knowledge of vector databases (e.g., Pinecone, Weaviate, FAISS)
• Experience with API integration and microservices architecture
• Strong understanding of data modelling, data warehousing, and data lakes
• Familiarity with CI/CD pipelines and DevOps practices

Preferred Qualifications

• Experience in banking or financial services environments
• Exposure to AI governance, model risk, and compliance frameworks
• Knowledge of MLOps and LLMOps practices
• Experience with streaming technologies (Kafka, Spark Streaming)
• Relevant certifications in Cloud, Data Engineering, or AI/ML

Key Competencies

• Strong problem-solving and analytical thinking
• Ability to work in complex, enterprise environments
• Excellent stakeholder engagement and communication skills
• High attention to detail and quality delivery
• Ability to work independently in a contracting environment

Deliverables

• Production-ready AI data pipelines and LLM applications
• Scalable and secure AI architecture implementations
• Documented and governed data and AI workflows
• Continuous improvement of AI platform performance and reliability