Senior AI Engineer

BILLIGENCE ASIA PTE. LTD.; Singapore; On-site; SGD 120,000 - 150,000; Full time

Job summary

A leading AI solutions company seeks an experienced architect for their GenAI solutions team in Singapore. The role includes designing scalable pipelines, overseeing LLM ops workflows, and leading cross-functional teams. Candidates should have at least 5 years of experience in AI/ML, a strong background in relevant technologies such as Python, and familiarity with cloud platforms. A Bachelor's or Master's degree in a related field is required. This position offers opportunities for significant impact in a fast-growing area of technology.

Qualifications

• Minimum 5 years’ experience architecting and deploying scalable AI/ML and GenAI solutions in enterprise environments.
• Deep expertise in machine learning, deep learning, and generative AI technologies.
• Strong familiarity with cloud platforms and MLOps practices for end-to-end machine learning lifecycle.

Responsibilities

• Architect and develop scalable GenAI pipelines, APIs, and microservices.
• Design robust prompt strategies for instruction-following and reasoning.
• Lead embedding model selection and tuning for optimization.

Skills

AI/ML solution architecture

Prompt engineering

Python

MLOps practices

Leadership

Real-time and batch AI applications

Education

Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering

Tools

FastAPI

Ray

LangServe

TensorFlow

PyTorch

AWS

Azure

GCP

MLflow

Databricks

Azure ML

Vertex AI

Job description

Minimum 5 years’ experience leading the design, development, and deployment of scalable AI/ML and GenAI solutions.

Key Responsibilities

• Architect and develop scalable GenAI pipelines, APIs, and microservices for real-time and batch AI applications using frameworks such as FastAPI, Ray, or LangServe.
• Design robust prompt strategies for instruction-following, reasoning, and multi-turn conversations, with a focus on RAG architectures for personalized, domain‑specific use cases.
• Lead embedding model selection and tuning to optimize semantic search and RAG performance.
• Oversee LLM Ops workflows, including model orchestration, evaluation, deployment, rollback strategies, and monitoring in production environments.
• Drive model fine‑tuning efforts to customize LLMs for proprietary datasets and regulated industries.
• Establish and govern AI testing frameworks, covering functional testing, regression testing, hallucination detection, safety filters, and output quality assessment.
• Implement enterprise‑grade observability, lineage tracking, and CI/CD automation using tools such as MLflow, Databricks, Azure ML, or Vertex AI.
• Lead continuous improvement initiatives based on telemetry, user feedback, and cost‑performance trade‑offs.
• Demonstrate expertise in Python, with deep proficiency in GenAI frameworks, vector search systems, and MLOps toolchains.

Qualifications

• Minimum 5 years’ experience architecting and deploying scalable AI/ML and GenAI solutions in enterprise environments.
• Deep expertise in machine learning, deep learning, and generative AI technologies, including hands‑on experience with frameworks like TensorFlow, PyTorch, and modern LLM orchestration tools.
• Strong familiarity with cloud platforms (AWS, Azure, GCP) and MLOps practices for end‑to‑end machine learning lifecycle management.
• Demonstrated leadership in managing agile, cross‑functional teams and collaborating with stakeholders.
• Significant experience in prompt engineering and prompt design for LLMs and GenAI applications.
• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field; advanced degrees or certifications (e.g., Azure AI Engineer) are advantageous.
• Experience with personalization, recommendation systems, or conversational AI is highly desirable.