Forward Deployed Engineer (AI)

Forward Deployed Engineer, AI Platform Full-time (Singapore) Role Summary Partner closely with enterprise customers to translate complex and ambiguous business challenges into clear, high-value agentic workflows with defined success criteria and evaluation methods. Lead the design, development, and delivery of LLM-powered agents that can reason, plan, and act across tools, APIs, and sensitive enterprise data sources with enterprise-grade reliability and performance. Build and ship features across the full product lifecycle from concept and designthrough production release. Own use cases end-to-end, including scoping, solution design, implementation, and delivery, while adapting across technical areas such as backend, frontend, and integrations where needed. Contribute to shared frameworks, patterns, and engineering practices that support consistent, scalable, and high-quality delivery across customers and internal teams. Drive clarity in ambiguous situations, align stakeholders, and help raise engineering quality across the organization. Bring strong hands-on experience in Python and production-grade software engineering, with the ability to write clean, testable, observable, and scalable code. Demonstrate experience building RAG and agentic applications using patterns such as ReAct or Plan-and-Execute, along with nowledge of frontier models, vector databases, and orchestration frameworks. Build robust evaluation frameworks to measu reagent accuracy, safety, latency, and overall performance beyond trial-and-error testing. Work confidently with enterprise stakeholders, lead technical discussions, and thrive in fast-paced, ambiguous environments with shifting priorities. Requirement: Hands-on experience building and deploying production-grade software in Python, with clean, testable, observable, and scalable code. Proven ability to develop high-performing RAG and agentic applications , including multi-step planning agents using ReAct or Plan-and-Execute patterns. Strong knowledge of the LLM ecosystem , including frontier models, vector databases, and orchestration frameworks. Experienced in building evaluation frameworks to measure accuracy, safety, latency, and performance. Comfortable working directly with enterprise customers, leading technical discussions, and translating ambiguous needs into clear technical specifications. Able to own use cases end-to-end and thrive in fast-paced, changing environments.