Senior GenAI Application Engineer

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

Job summary

SAKSOFT LIMITED is seeking a Senior GenAI Application Engineer in Singapore to design, build and scale production-grade GenAI applications. You will work with LangGraph, LangChain and open weight models, crafting agentic workflows and prompt orchestration while integrating with enterprise systems and data sources.

The role demands deep backend expertise, experience with Kubernetes/OpenShift, and a pragmatic delivery mindset in a fast-moving environment.

Qualifications

• 6+ years of software engineering, with GenAI application development.
• Production-grade GenAI applications experience required.
• Hands-on with LangGraph/LangChain or similar orchestration frameworks.
• Understanding of RAG, agentic workflows, tool calling and context management.
• Experience integrating LLMs via APIs and enterprise data sources.
• Open weight models experience or demonstrated interest.
• Strong backend skills in Python/Java and API design.
• Familiar with Kubernetes or OpenShift for deployment.
• Proficient in observability, logging, tracing and troubleshooting.

Responsibilities

• Build and improve GenAI applications using LangGraph or LangChain.
• Work with open weight models, hosted LLMs and serving patterns.
• Develop agentic workflows, RAG, tool calling and prompt orchestration.
• Integrate GenAI apps with enterprise APIs, data sources and infra.
• Ensure production quality with logging, tracing, evaluation and fallbacks.
• Collaborate across application, data, platform, security and infra teams.
• Maintain high ownership, curiosity and delivery focus.

Skills

GenAI development

LangGraph

LangChain

RAG

agentic workflows

prompt orchestration

API integration

open weight models

Python/Java

distributed systems

observability

logging/tracing

Kubernetes/OpenShift

code quality

Tools

vLLM

Redis

Langfuse

Elastic

Job description

Experience

6+ Years

Role

Senior GenAI Application Engineer

Key Skills

• Production GenAI Application Engineering
• LangGraph, LangChain, RAG and Agentic Workflows

Responsibilities

• 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.
• 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:

1. 6 or more years of software engineering experience, preferably with recent hands on experience in GenAI application development.
2. Proven experience building production grade GenAI applications, not only prototypes, experiments or demos.
3. Strong hands on experience with LangGraph, LangChain or similar orchestration frameworks.
4. Practical understanding of RAG, agentic workflows, tool calling, prompt orchestration and context management.
5. Experience integrating LLMs into real applications using APIs, backend services and enterprise data sources.
6. Experience with open weight models or strong interest backed by hands on experimentation.
7. Strong backend engineering skills using Python, Java or similar languages.
8. Good understanding of API design, distributed systems and production resilience patterns.
9. Experience with observability, logging, tracing and troubleshooting for GenAI or backend applications.
10. Familiarity with containerised deployment environments such as Kubernetes or OpenShift.
11. Ability to write clean, maintainable and testable code.
12. Strong analytical, debugging and troubleshooting skills.
13. High ownership, high curiosity and genuine interest in building useful AI products.
14. Ability to work in a fast moving environment with incomplete information and evolving requirements.
15. Strong communication skills, with the ability to challenge weak designs and coordinate across business, application, data, infrastructure and security teams.

Nice to Have

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