Agentic AI / ML Engineer

Epergne Solutions; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

Epergne Solutions in Singapore seeks an experienced Agentic AI / ML Engineer to design, build, and maintain scalable AI systems using modern LLM frameworks and MLOps practices.

You will collaborate across teams to translate business needs into production-ready AI solutions, developing reusable components and robust pipelines with LangGraph workflows and A2A orchestration.

Qualifications

• Proficiency in Python, including unit testing with pytest.
• Experience with SQL and ML libraries (scikit-learn, PyTorch, TensorFlow).
• Hands-on experience designing and orchestrating agentic AI systems.
• Strong understanding of LangGraph workflows and reusable components.
• Good prompt engineering skills for LLM control.
• Practical experience with Git and CI/CD pipelines (GitLab preferred).
• Knowledge of MLOps tools (MLflow, Kubeflow, Azure ML).
• Familiarity with Azure cloud and/or Kubernetes environments.

Responsibilities

• Design and develop reusable agentic AI workflows using LangGraph and LLMs.
• Implement A2A orchestration patterns.
• Develop clean, maintainable Python code with comprehensive pytest coverage.
• Craft and optimize LLM prompts for accuracy, consistency, and reliability.
• Build reusable components for data transformation and processing.
• Use Git and GitLab CI/CD to automate build, test, and deployment pipelines.
• Translate business requirements into technical specifications.
• Adapt to evolving project needs and take on additional responsibilities as required.

Skills

Python

pytest

prompt engineering

LangGraph

A2A orchestration

LLM workflows

problem solving

fast-changing environment

Tools

Git

GitLab CI/CD

MLflow

Kubeflow

Azure ML

Azure cloud

Kubernetes

PyTorch

TensorFlow

scikit-learn

LangGraph

Job description

Job role

- Agentic AI / ML Engineer

Job Location

- Singapore

Experience

- 6-12 Years

Job Summary

Design, build, and maintain scalable agentic AI solutions using modern LLM frameworks and MLOps practices. Collaborate with cross-functional teams to translate business needs into reliable, production-ready AI systems.

Job Roles & Responsibilities

• Design and develop reusable agentic AI workflows using LangGraph and LLMs
• Implement Agent-to-Agent (A2A) orchestration patterns
• Develop clean, maintainable Python code with comprehensive pytest coverage
• Craft and optimize LLM prompts for accuracy, consistency, and reliability
• Build reusable components for data transformation and processing
• Use Git and GitLab CI/CD to automate build, test, and deployment pipelines
• Translate business requirements into technical specifications
• Adapt to evolving project needs and take on additional responsibilities as required

Job Skills & Requirements

• Proficiency in Python, including unit testing with pytest
• Experience with SQL and ML libraries (scikit-learn, PyTorch, TensorFlow)
• Hands-on experience designing and orchestrating agentic AI systems
• Strong understanding of LangGraph workflows and reusable components
• Good prompt engineering skills for LLM control
• Practical experience with Git and CI/CD pipelines (GitLab preferred)
• Knowledge of MLOps tools (MLflow, Kubeflow, Azure ML)
• Familiarity with Azure cloud and/or Kubernetes environments
• Strong problem-solving and logical reasoning skills
• Ability to work effectively in a fast-changing environment

Good to Have

• Experience with Java (Spring Boot) and/or React
• Exposure to financial domain data (e.g., risk, trading, KYC)
• Advanced experience with LangGraph and A2A orchestration