Design, build, and deploy production AI applications, including retrieval pipelines, LLM orchestration, APIs, and user interfaces. Own the software lifecycle, integrate model and vector database technologies, evaluate performance, manage CI/CD and cloud operations, and contribute reusable platform components. Collaborate with business teams and AI product managers while documenting architecture, communicating risks, and improving applications after launch.
As a part of the Central AI-Core Studio & Delivery team, this role would require you to drive the design, build, and production delivery of AI-enabled applications for our core business lines.
Key Responsibilities
- Design and build end-to-end AI-powered applications, including retrieval pipelines, LLM orchestration layers, backend APIs, and user-facing interfaces.
- Own the full software development lifecycle from requirements and architecture through testing, deployment, and post-launch iteration.
- Integrate LLM APIs, vector databases, and retrieval-augmented generation into production applications, applying agentic orchestration where needed.
- Evaluate AI models and retrieval approaches, defining evaluation criteria and iterating on production performance data.
- Own CI/CD pipelines, containerisation, observability, and secure cloud deployment, and document architectural decisions and trade-offs.
- Contribute reusable components and shared engineering standards to the AI platform.
- Work directly with business teams and AI PMs in a forward-deployed model, communicating progress and risks to technical and non-technical stakeholders.
About you
- A track record of shipping production software that people rely on - applications you’ve built, debugged, and improved under real operating conditions.
- Strong Python proficiency, with experience in REST APIs, cloud deployment, and containerisation.
- Hands-on experience with LLM APIs (OpenAI, Anthropic, or equivalent) and retrieval/vector database systems.
- Solid understanding of software architecture, testing practices, and production operations.
- It will be advantageous if you have experience in agentic orchestration frameworks (LangChain, LangGraph, AutoGen) and frontend development with React and TypeScript.
- It will be advantageous if you are familiar with the Architecture, Engineering and Construction industry, infrastructure, or enterprise workflow domains, and AWS, Azure, or GCP environments.
We value equity, diversity and inclusion and are committed to creating a work environment where everyone feels a sense of belonging and is empowered to do their best. We recognise the importance of a diverse and inclusive workplace to drive innovation and shared learning across our growing global network.
Join us and be part of a culture where we rise together, deliver excellence, and expand what’s possible.
At Surbana Jurong, we put talent, hard work, teamwork and a fun workplace together to approach problems and solve them creatively and collaboratively. Join us in making a positive impact on the world!
Surbana Jurong Singapore, Singapore, SGP Office
Singapore, Singapore
Similar Jobs
Artificial Intelligence • Consumer Web • Digital Media • Information Technology • Social Impact • Software
Lead the AI Quality engineering team while remaining hands-on building evaluation infrastructure, CI/CD pipelines, scorers, datasets, observability tooling, and diagnostic systems for production AI agents. Design experiments across prompts and models, improve agent reliability, latency, and cost, develop annotation and simulation workflows, and partner with AI Core engineering to validate product changes.
Top Skills:
Ai AgentsAnnotation WorkflowsBraintrustCachingCi/CdDatasetsEvaluation InfrastructureLangsmithLlmsModel RoutingObservability ToolingPythonRuby On Rails
Artificial Intelligence • Consumer Web • Digital Media • Information Technology • Social Impact • Software
Lead the AI Quality engineering team while remaining hands-on building evaluation infrastructure, observability tooling, diagnostic systems, datasets, annotation workflows, and CI/CD pipelines for production AI agents. Run experiments across prompts, models, routing, caching, and agent harnesses to improve quality, latency, and cost. Partner with AI Core engineering and manage technical direction and team priorities.
Top Skills:
Ai AgentsBraintrustCi/CdLangsmithLlmsPythonRuby On Rails
Fintech • Professional Services • Consulting • Energy • Financial Services • Cybersecurity • Generative AI
Build and deploy production-grade AI solutions for insurance and financial services, including multi-agent workflows, LLMs, RAG systems, neural networks, and automation pipelines. Responsibilities include model training and optimization, backend development, cloud deployment, production monitoring, regulatory compliance, ethical AI, troubleshooting, code reviews, and collaboration with technical and business stakeholders.
Top Skills:
AdkAWSAzureCcpaCi/CdDockerGdprGitGCPHadoopJavaKubernetesLangchainLanggraphLlmsMlopsNext.JsNode.jsNoSQLPythonRagReactSparkSQL
What you need to know about the Singapore Tech Scene
The digital revolution has driven a constant demand for tech professionals across industries like software development, data analytics and cybersecurity. In Singapore, one of the largest cities in Southeast Asia, the demand for tech talent is so high that the government continues to invest millions into programs designed to develop a talent pipeline directly from universities while also scaling efforts in pre-employment training and mid-career upskilling to expand and elevate its workforce.
