AI Engineer

SAKSOFT PTE LIMITED; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

SAKSOFT PTE LIMITED in Singapore seeks a Senior AI Engineer to design, build, and maintain production-grade GenAI applications. You will operate at the intersection of software engineering, GenAI development, enterprise integration and delivery to enterprise users.

Applicants should bring hands-on experience with LangGraph, LangChain, RAG, tool orchestration and API-driven integrations, with a pragmatic, delivery-focused mindset. This is a full-time, on-site role in Singapore.

Qualifications

• 6+ years of software engineering experience, with hands-on GenAI app development.
• Proven track record building production GenAI applications, not just demos.
• Strong experience with LangGraph/LangChain, RAG and agentic workflows.

Responsibilities

• Build and improve GenAI applications for production, with reliability and observability.
• Work with open weight models, hosted LLMs and model serving patterns.
• Develop agentic workflows, retrieval augmented generation and tool calling.
• Integrate GenAI apps with enterprise systems, APIs and data sources.
• Ensure production quality: logging, tracing, evaluation and fallback handling.
• Collaborate across application, data, platform, security and infra teams.

Skills

GenAI application engineering

LangGraph

LangChain

RAG

Agentic workflows

Python

Java

APIs

Enterprise integration

Job description

Experience : 6+ Years

Role : AI Engineer

Key Skills :

• Production GenAI Application Engineering
• LangGraph, LangChain, RAG and Agentic Workflows
• Python,Java, APIs and Enterprise Integration

Responsibilities:

We are looking for a Senior GenAI Application Engineer who operates effectively at the intersection of software engineering, GenAI application development, enterprise integration and production delivery . This is not a pure research role. It is not a prompt engineering only role. The successful candidate will help design, build and improve production grade GenAI applications that are reliable, observable, maintainable and useful to real enterprise users.

• Build and improve GenAI applications using frameworks such as LangGraph, LangChain or similar orchestration tools .
• Work with open weight models , hosted LLMs and model serving patterns.
• Develop agentic workflows, retrieval augmented generation, tool calling and prompt orchestration.
• Integrate GenAI applications with enterprise systems, APIs, data sources and operational platforms.
• Engineer solutions for production quality, including logging, tracing, evaluation, fallback behaviour and troubleshooting.
• Bring a strong can do attitude , enthusiasm, curiosity and practical delivery mindset.

Finance or banking experience is not required . What matters more is hands on experience building real GenAI applications, strong engineering judgement and the ability to deliver in a complex enterprise environment.

What Matters Most

• Strong hands on experience building production grade GenAI applications .
• Practical experience with LangGraph, LangChain, agentic workflows, RAG and tool calling .
• Understanding of open weight models and how to integrate them into real applications.
• Ability to challenge weak designs and propose better ones.
• Strong engineering discipline around reliability, testing, observability and maintainability.
• Ability to work across application, data, platform, security and infrastructure teams.
• Enthusiastic, energetic and willing to get into the details.
• Pragmatic approach to delivery, not over engineering, not hype driven.

Requirements:

Below are the key skillsets required for the role:

• 6 or more years of software engineering experience , preferably with recent hands on experience in GenAI application development.
• Proven experience building production grade GenAI applications , not only prototypes, experiments or demos.
• Strong hands on experience with LangGraph, LangChain or similar orchestration frameworks .
• Practical understanding of RAG, agentic workflows, tool calling, prompt orchestration and context management .
• Experience integrating LLMs into real applications using APIs, backend services and enterprise data sources.
• Experience with open weight models or strong interest backed by hands on experimentation.
• Strong backend engineering skills using Python, Java or similar languages .
• Good understanding of API design, distributed systems and production resilience patterns.
• Experience with observability, logging, tracing and troubleshooting for GenAI or backend applications.
• Familiarity with containerised deployment environments such as Kubernetes or OpenShift .
• Ability to write clean, maintainable and testable code.
• Strong analytical, debugging and troubleshooting skills.
• High ownership, high curiosity and genuine interest in building useful AI products.
• Ability to work in a fast moving environment with incomplete information and evolving requirements.
• Strong communication skills, with the ability to challenge weak designs and coordinate across business, application, data, infrastructure and security teams.

Nice to Have

• Experience with DeepAgent or similar agent frameworks.
• Experience with Langfuse, Elastic or similar observability and search tools.
• Experience with Redis for caching, conversation state, rate limiting, queue backed workflows or low latency GenAI application patterns.
• Experience with vLLM or similar inference serving frameworks for running open weight models.
• Experience deploying GenAI workloads on cloud or container platforms.