Full Stack Engineer

• Provide technical leadership to an agile, cross-functional development team • Define and communicate technical vision across multiple workstreams • Design scalable, secure, and resilient architectures for search and AI-powered systems • Make architectural trade-offs balancing performance, cost, reliability, and security • Collaborate with other Tech Leads to plan technical spikes and long-term technical strategy beyond sprint scope • Identify technical risks early and lead mitigation strategies • Architect systems leveraging: • LLM integrations (e.g., Azure OpenAI, OpenAI APIs, etc.) • Retrieval-Augmented Generation (RAG) • Semantic search and vector databases • Establish guardrails for AI systems including: • Evaluation frameworks • Observability and monitoring • Data governance and security considerations • Guide the team from experimentation → prototype → production-ready AI systems • Evaluate emerging AI technologies and assess suitability for public sector use cases • Champion Agile technical practices (TDD, pair programming, refactoring, CI/CD) • Lead DevOps adoption including build, release automation, and infrastructure improvements • Oversee automated testing strategy (unit, integration, performance) • Lead resolution of technical blockers and retrospective improvements • Ensure engineering standards are upheld across the team • Work closely with Product Owners and Business Analysts to prioritise business stories and technical investments • Collaborate with UX Designers for feasibility studies and solution estimation • Partner with Delivery Managers on long-term planning, system integrations, and resource forecasting • Represent the development team in governance and stakeholder meetings • Mentor and coach engineers to grow both technically and professionally How to Succeed • 5–7+ years of experience in web application development • Proven experience leading agile development teams • Strong hands-on experience with: • Node.js, TypeScript • Cloud platforms (Azure, AWS, GCP) • SQL & NoSQL databases • CI/CD pipelines • DevOps practices • Designed or led systems involving: • Search engines (crawl, index, ranking, relevance tuning) • Semantic search or vector search • RAG architectures • Production experience integrating LLMs into applications • Experience managing AI-related trade-offs: • Latency vs cost • Accuracy vs hallucination risks • Prompt engineering strategies • Model evaluation methodologies • Understanding of AI system governance, security, and responsible AI practices • Strong coaching and mentoring capabilities • Comfortable leading technical discussions and influencing stakeholders • Proactive self-starter with strong ownership mindset • Passionate about continuous improvement • Curious about emerging technologies and willing to experiment responsibly • Strong communication and stakeholder management skills • Meticulous attention to quality and engineering standards