Expert Full Stack Developer

Are you a tech powerhouse who loves solving complex problems, building smart solutions and pushing the boundaries of what software can do? We're looking for an Expert Full Stack Developer who can combine strong software engineering skills with modern data engineering, cloud technologies and AI innovation.

You'll work on exciting, enterprise-scale technology solutions involving static vehicle master data, data platforms, integrations and cloud migration. This is your opportunity to turn big ideas into production-ready solutions, experiment with emerging technologies and help shape the future of AI-enabled software engineering.

If Python, Java, cloud architecture and AI get you excited, keep reading!

• Expert software engineering capability with a strong record of designing, building, testing, deploying and operating production-grade enterprise solutions.
  
• Advanced Python and Java development, including clean code, object-oriented and functional design, concurrency, performance optimisation, packaging and dependency management.
  
• Strong data engineering capability across batch and event-driven ingestion, ETL/ELT, data transformation, data modelling, data quality, metadata, lineage and large-scale processing.
  
• Hands-on experience with APIs, microservices and integration patterns, including REST, GraphQL, messaging, Kafka and contract-first development.
  
• Cloud-native engineering experience, preferably AWS, including serverless, containers, storage, databases, queues, identity, networking and observability.
  
• AI engineering capability covering LLM-based applications, agents, retrieval-augmented generation, prompt and context engineering, tool integration, evaluation, guardrails and human approval gates.
  
• Ability to use AI-assisted development responsibly across specification, coding, review, testing, documentation and operations while retaining accountability for correctness and security.
  
• Strong systems thinking: understand end-to-end behaviour, dependencies, feedback loops, failure modes, trade-offs and the wider organisational impact of technical decisions.
  
• Out-of-the-box problem solving with the ability to simplify complex problems, challenge assumptions, prototype alternatives and convert successful approaches into reusable patterns.
  
• Engineering excellence across automated testing, secure coding, code review, CI/CD, Infrastructure as Code, version control and production-readiness practices.
  
• Ability to translate business and system requirements into maintainable architecture, technical designs, implementation plans and measurable engineering outcomes.
  
• Clear communication and technical leadership across multidisciplinary, distributed and multicultural teams.
  
• Adaptability to perform additional tasks under the Agile Working Model (AWM) Charter.
  

• Experience in automotive, mobility, manufacturing or a large multinational enterprise environment.
  
• Knowledge of enterprise data products, federated data platforms, Digital Twin concepts, semantic models, knowledge graphs and ontologies.
  
• Experience with Apache Spark, Kafka, SQL and NoSQL technologies, and modern lakehouse or warehouse patterns.
  
• Exposure to TypeScript/JavaScript and modern frontend frameworks such as Angular or React.
  
• Experience with Docker, Kubernetes, Terraform, GitHub Enterprise and GitHub Actions.
  
• Knowledge of observability, SRE, incident management, resilience engineering and service management practices.
  
• Understanding of privacy, information protection, data governance, retention, cross-border data handling and responsible AI controls.
  
• Ability to mentor engineers, lead technical design reviews and improve engineering standards across teams.
  
• High ownership, curiosity, integrity, resilience and a continuous-learning mindset.
  
• Willingness and ability to travel internationally when required.
  

• Relevant degree or diploma in Computer Science, Software Engineering, Information Technology, Data Engineering or a related field.
  
• Typically seven or more years of relevant software engineering experience, including responsibility for complex production systems.
  
• Demonstrable expert-level delivery using Python and/or Java, with strong data and integration engineering experience.
  
• Practical evidence of AI-assisted or AI-native engineering, including evaluation, governance and accountable human review.
  
• AWS, Java, Python, data engineering, architecture, DevOps, Kubernetes, Terraform, Agile or AI-related certifications are advantageous.