Full Stack Engineer

Job Description:

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

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