Full Stack Software Engineer - Applied AI

About the OpportunityOur client, a technology consultancy specialising in cloud, data, and AI-driven solutions for enterprise customers, is expanding its engineering team. This role sits at the intersection of traditional full stack development and applied AI — building products that incorporate agentic workflows and LLM-powered capabilities, engineered to production standards of reliability and scale.The successful candidate will contribute across the full software lifecycle, from system design and implementation through to operational ownership of AI-powered services in production.Key ResponsibilitiesSoftware EngineeringDevelop and maintain full stack applications using Python, JavaScript/TypeScript, and GoDesign scalable system architecture, including service boundaries, caching, queuing, and failure handlingDesign efficient database schemas and queriesDefine and document API contracts (REST, gRPC, or GraphQL) for internal and external consumersContainerise and deploy services using Docker and KubernetesApplied AI & Agentic SystemsDesign and implement agentic AI workflows, including multi-step task execution, tool use, memory, and multi-agent orchestrationIntegrate large language models, third-party AI APIs, and internal data sources into production systemsAI OperationsBuild and maintain operational pipelines for LLM-based systems, covering deployment, monitoring, evaluation, prompt and model versioning, and cost trackingOwn the reliability and performance of production systems, including monitoring, alerting, and incident responseCollaboration & GovernanceWork closely with product, research, and engineering stakeholders across the SDLCParticipate in code reviews, architecture discussions, and technical planningContribute to technical documentation and runbooks to support long-term maintainabilityCandidate Requirements2–6 years of professional experience building full stack applications, backend services, and production-grade software systemsStrong working proficiency in Python and JavaScript/TypeScriptWorking knowledge of Go, or demonstrated ability to acquire it quicklyPractical experience with infrastructure-as-code tools such as Terraform (Ansible advantageous)Experience with cloud and/or on-premise infrastructureProficiency with Docker; working knowledge of Kubernetes advantageousDemonstrated experience building or operating AI-powered systems, agentic workflows, or LLM-based applicationsFamiliarity with agent orchestration principles — multi-step reasoning, tool use, memory, multi-agent designWorking knowledge of MLOps/AIOps practices, including model or prompt versioning, evaluation pipelines, and observabilitySolid understanding of system design fundamentals, including scalability, reliability, and distributed systems trade-offsStrong communication skills and a demonstrated sense of technical ownershipAdvantageousDirect experience with LLM providers such as OpenAI, Anthropic, or Azure OpenAI, or with open-source modelsExperience with RAG, embeddings, or vector databasesUnderstanding of security principles applicable to both traditional and AI systemsPrior experience within a startup or applied AI product environmentWhat the Role OffersThe opportunity to build production-grade products combining software engineering with applied AIExposure to agentic AI systems and LLM-powered infrastructure at scaleA flat, low-bureaucracy team structure that supports rapid executionClose collaboration with product, research, and engineering functions from concept through to deploymentStructured learning and development support, including courses and conferencesCompetitive remuneration and benefitsSTReg No. R1768414BeathChapman Pte LtdLicence no. 16S8112