Our client is seeking a GenAI Full Stack Developer to design, build, and scale enterprise AI applications powered by Large Language Models, Retrieval-Augmented Generation (RAG), and Azure-native cloud services.This role is ideal for someone with strong backend engineering and system design capability who enjoys building production-grade AI systems across the full stack. You will work closely with product, UX, platform, and engineering teams to deliver secure, scalable, and reliable AI-powered applications with a strong focus on performance, maintainability, and responsible AI practices.Full Stack DevelopmentBuild and maintain modern web applications using React, Next.js, Angular, or similar frameworksDesign and develop scalable backend APIs and AI orchestration services using advanced Python, FastAPI, Node.js, Java, or .NETDevelop cloud-native and serverless applications using Azure services such as Azure Functions, API Management, Logic Apps, and Azure Service BusImplement secure authentication and authorisation systems including OAuth2, OpenID Connect, JWT, and RBACApply software engineering best practices including testing, CI/CD, documentation, code reviews, and modular architectureGenAI & RAG EngineeringDesign and implement AI-powered capabilities such as assistants, semantic search, summarisation, workflow automation, and intelligent retrieval systemsBuild and optimise enterprise-grade RAG architectures including ingestion pipelines, chunking strategies, embeddings, vector search, hybrid retrieval, reranking, grounding, and hallucination mitigationIntegrate with LLM providers and orchestration frameworks including Azure OpenAI, OpenAI, Anthropic, Hugging Face, LangChain, Semantic Kernel, or LlamaIndexDevelop prompt engineering strategies, tool/function calling workflows, guardrails, moderation pipelines, and output validation systemsImplement observability and evaluation mechanisms for monitoring LLM quality, latency, and reliabilityData & Enterprise IntegrationsIntegrate AI applications with enterprise systems such as SharePoint, Salesforce, ServiceNow, and internal APIsDevelop data ingestion, enrichment, transformation, and retrieval pipelinesWork with relational, NoSQL, and vector databases including PostgreSQL, Redis, Azure AI Search, Pinecone, Elasticsearch, or similar technologiesEnsure strong governance, privacy, and security controls for enterprise and sensitive dataPerformance, Security & ReliabilityOptimise LLM performance, scalability, latency, and operational cost through caching, batching, streaming, and token optimisationDesign resilient distributed systems using retries, fallbacks, circuit breakers, and graceful degradation patternsImplement logging, monitoring, tracing, and observability solutions using OpenTelemetry, Application Insights, Grafana, or similar toolingApply responsible AI principles including privacy controls, auditability, bias mitigation, and secure AI implementation practicesParticipate in system design discussions and contribute to scalable cloud architecture decisionsRequired Skills & Experience3 to 8+ years of full stack software engineering experienceAdvanced Python programming and backend engineering capabilityDeep hands-on experience building production-grade RAG systems and LLM-enabled applicationsStrong experience with Azure-native architecture and serverless servicesStrong understanding of REST APIs, microservices, distributed systems, and cloud-native designExperience designing secure authentication and API security solutions using OAuth2, OpenID Connect, JWT, and RBACStrong system design and scalable architecture capabilityExperience with CI/CD pipelines, testing frameworks, version control, and agile delivery methodologiesPreferred QualificationsExperience with Azure OpenAI, Azure AI Search, Azure Functions, Azure API Management, Azure Key Vault, and Azure Service BusFamiliarity with LangChain, Semantic Kernel, LlamaIndex, or similar AI orchestration frameworksExperience with vector databases, embedding models, reranking, and grounding techniquesExperience with Docker, Kubernetes, Terraform, or Infrastructure as Code practicesUnderstanding of enterprise security, compliance, and governance frameworksExperience designing event-driven and serverless AI systems on AzureTech StackFrontend: React, Next.js, TypeScript, TailwindBackend: Python (FastAPI), Node.js, .NET APIsAI Stack: Azure OpenAI, LangChain, Semantic Kernel, RAG PipelinesData: PostgreSQL, Redis, Azure AI Search, Vector DatabasesCloud & DevOps: Azure Functions, Azure API Management, GitHub Actions, Docker, Kubernetes, OpenTelemetry
3 days ago