Senior AI Engineer

BILLIGENCE ASIA PTE. LTD.; Singapore; On-site; SGD 100,000 - 150,000; Full time

Job summary

A leading AI technology firm in Singapore seeks an experienced professional to lead the design and deployment of scalable AI/ML and GenAI solutions. The candidate must have over 5 years of expertise in architecting AI systems and experience with technologies such as TensorFlow and cloud platforms. This role includes responsibilities like developing GenAI pipelines, leading model tuning, and overseeing AI testing frameworks.

Qualifications

• Minimum 5 years’ experience in AI/ML solution deployment.
• Expertise in deep learning and generative AI technologies.
• Experience with personalized and conversational AI projects.

Responsibilities

• Architect and develop scalable GenAI pipelines and APIs.
• Lead embedding model selection and tuning for semantic search.
• Implement observability and CI/CD automation in AI workflows.

Skills

AI/ML development

GenAI frameworks

Python

Prompt engineering

Cloud platforms

Education

Bachelor’s or Master’s degree in Computer Science or related field

Tools

FastAPI

Ray

TensorFlow

PyTorch

MLflow

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.