Full Stack Developer (Expert)- Python, Java, Data Engineering & AI Engineering

Introduction

We are seeking an expert-level Full Stack Developer with strong software engineering, data engineering, cloud-native development and AI engineering capabilities to design, develop and operate secure, scalable enterprise technology solutions.

This role offers the opportunity to work on complex, production-grade systems involving static vehicle data, enterprise data products, system integration and cloud-based data platforms. The successful candidate will contribute to modernising data capabilities, building AI-enabled solutions and improving engineering practices across a complex enterprise environment.

The ideal candidate combines advanced Python and Java development with strong data pipeline engineering, API and microservices integration, cloud technologies and practical experience building AI-enabled applications, including large language model (LLM) solutions and retrieval-augmented generation (RAG).

Duties & Responsibilities

Design, build, test, deploy and operate secure, scalable and maintainable DVF software, data products and platform capabilities.

Own technical delivery from discovery and design through implementation, release, monitoring, support and continuous improvement.

Develop high-quality Python and Java components for data processing, APIs, microservices, automation,

integration and platform services.

Engineer reliable batch and event-driven data pipelines with clear contracts, validation, observability, lineage and recoverability.

Build AI-enabled solutions and reusable engineering accelerators, including agents, RAG patterns, tools,

prompts, context packages, evaluations and guardrails.

Apply specification-driven and AI-assisted development practices, using human approval gates for architecture, security, quality and production changes.

Take a systems view of DVF, identifying cross-subsystem impacts, dependencies, bottlenecks, failure modes and opportunities to simplify the landscape.

Challenge conventional approaches, rapidly prototype options and turn validated ideas into governed, reusable patterns and production solutions.

Produce and maintain architecture views, technical designs, interface contracts, decision records, runbooks and implementation documentation.

Implement automated unit, integration, contract, component, performance and regression tests as appropriate.

Build and maintain CI/CD pipelines, Infrastructure as Code, security scanning, dependency management and quality gates.

Ensure solutions meet requirements for security, privacy, data governance, information protection, auditability,

resilience and operational support.

Use telemetry and operational feedback to improve reliability, performance, cost efficiency and developer experience.

Lead code reviews and technical design reviews, mentor engineers and promote consistent engineering standards and reusable solutions.

Collaborate with Product Owners, Systems Analysts, Architects, Data Engineers, Test Engineers, Operations and Security to resolve ambiguity and deliver measurable outcomes.

Support PI planning and sprint execution by refining technical work, identifying dependencies and risks, and providing realistic implementation options.

Communicate technical decisions, progress, risks and trade-offs clearly to technical and non-technical stakeholders.

Contribute to the evolution of DVF into an AI-native, federated data-product organisation with shared platform,

quality and AI enablement capabilities.

Desired Experience & Qualification

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.

Package & Remuneration

Cutting edge global IT system landscape and processes

Flexible working of 1960 hours in a 12-month period

High Work-Life balance

Remote / On-site work location flexibility

Highly motivating, energetic, and fast-paced working environment

Modern, state-of-the-art offices

Dynamic Global Team collaboration

Application of the Agile Working Model Methodology

Interested?