Senior Associate/Assistant Vice President, Full Stack Agentic AI Engineer

Temasek International Pte. Ltd.; Singapore; On-site; SGD 120,000 - 170,000; Full time

Job summary

Temasek International Pte. Ltd. is pursuing scalable AI/ML systems in production, delivering agentic AI and LLM-powered products with strong observability and risk controls.

The role requires 4-8 years of software engineering, deep full-stack skills, and hands-on experience with LangChain, OpenAI/Anthropic SDKs, and modern AI tooling to ship real user-facing solutions in regulated financial contexts.

Qualifications

• 4-8 years of software engineering experience with strong full-stack depth and at least 2 years focused on AI/ML system engineering.
• Hands-on experience with modern agentic AI frameworks: LangChain, LangGraph, AutoGen, CrewAI, or equivalent; familiarity with Anthropic and OpenAI SDKs and their tool-calling and streaming APIs.
• Experience shipping production AI systems with real users, including monitoring, incident response, and continuous improvement.
• Experience in financial services or data-intensive regulated industries is advantageous.

Skills

Full-stack development

AI/ML systems

LangChain, LangGraph, AutoGen, CrewAI

Anthropic/OpenAI SDKs

Python, FastAPI, asyncio, Pydantic

TypeScript/JavaScript, React, Next.js,

Tools

Docker

Kubernetes

AWS/Azure/GCP

dbt/Airflow

LangSmith/LangFuse

Job description

Experience and background

• 4-8 years of software engineering experience with strong full-stack depth and at least 2 years focused on AI/ML system engineering - ideally building and operating agentic AI or LLM-powered products in production.


• Hands-on experience with modern agentic AI frameworks: LangChain, LangGraph, AutoGen, CrewAI, or equivalent; strong familiarity with the Anthropic and OpenAI SDKs and their tool-calling and streaming APIs.


• Demonstrated experience shipping production AI systems with real users - not research experiments, but deployed products with monitoring, incident response, and continuous improvement cycles.


• Experience in financial services, fintech, or data-intensive regulated industries is advantageous.

Technical capabilities

• Languages and frameworks: Python (primary, including FastAPI, asyncio, Pydantic), TypeScript/JavaScript (React, Next.js, Node.js); comfortable across the stack without deep specialisation limiting your ability to contribute end-to-end.


• AI/ML stack: LLM integration (Anthropic Claude, OpenAI GPT-4o, Google Gemini), embedding models, vector databases, RAG pipeline components, evaluation frameworks (LangSmith, RAGAS, custom), and observability tooling (Helicone, LangFuse, or equivalent).


• Infrastructure and DevOps: containerisation (Docker, Kubernetes), cloud deployment (AWS, Azure, or GCP), CI/CD pipelines, secrets management, and basic security hygiene for AI systems (input sanitisation, output validation, access-scoped tool permissions).


• Data engineering basics: SQL proficiency, familiarity with data pipeline tooling (dbt, Airflow, or equivalent), and ability to design data access patterns optimised for AI consumption.