Technical Lead – AI Personalisation

Role Overview

• Lead the end-to-end design, architecture, and delivery of AI products including chatbots, LLM integrations, and analytics platforms
• Define and uphold technical standards, coding practices, and architectural patterns across the team
• Provide hands-on technical guidance and mentorship to a cross-functional team of engineers and data practitioners
• Drive technical discovery, proof-of-concept initiatives, and technology evaluations for emerging AI capabilities
• Collaborate closely with Product Owners, Data Architects, and AI Personalisation leads to align delivery with business objectives
• Architect and deliver LLM-based products including RAG pipelines, prompt engineering, knowledge-base retrieval, and dynamic conversational agents
• Design and implement ETL/ELT pipelines for ingesting, transforming, and serving structured and unstructured data
• Develop and maintain Python-based data processing scripts, ML model wrappers, and AI orchestration layers
• Manage API lifecycle and integration patterns using Gravitee API Gateway
• Implement secure, performant RESTful APIs for consumption by frontend teams, chatbot engines, and third-party integrations
• Design and enforce API security architecture standards across all services
• Architect and manage cloud infrastructure on AWS, ensuring scalability, security, and cost efficiency
• Oversee containerised workload deployment using Amazon ECS with AWS Fargate
• Lead observability strategy using Dynatrace: including full-stack monitoring, distributed tracing, synthetic monitoring, alerting, and dashboards
• Own and evolve Azure DevOps (ADO) pipelines for continuous integration and continuous delivery across all team services

Requirements

• Degree in Computer Science, Software Engineering, Information Technology, or equivalent
• 8+ years of software engineering experience, with at least 2 years in a technical lead or senior engineering role
• Proven experience building and deploying AI/ML products in a production environment
• Strong background in Java Spring Boot backend development and microservices architecture
• Hands-on experience with Python for data engineering, scripting, and AI integration
• Demonstrable expertise in API security architecture OAuth 2.0, OIDC, JWT, session management, and OWASP API Top 10
• Experience with Gravitee API Gateway or equivalent API management platforms
• Hands-on experience with Amazon API Gateway, ALB, Route 53, and AWS networking
• Proficiency in Dynatrace for APM, distributed tracing, and observability
• Hands-on experience with Azure DevOps for CI/CD pipeline design and sprint management
• Deep understanding of AWS cloud services and cloud-native design patterns
• Experience working in Agile/SAFe delivery frameworks (PI Planning, Scrum, Kanban)

Tech Stack

• AWS
• Azure
• Cloud
• ETL
• Java
• Microservices
• Python
• Spring
• Spring Boot
• SpringBoot

Benefits

• Health insurance
• Flexible working hours
• Professional development opportunities