Role: Full stack Software Engineer (GenAI Platforms)
JD:
● 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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