Forward Deployed Engineer (AI) - Part-Time

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.