Senior AI Engineer

BILLIGENCE CONSULTANCY PTE. LTD.; Singapore; On-site; SGD 100,000 - 130,000; Full time

Job summary

A technology consulting firm in Singapore seeks an experienced AI Architect to design scalable GenAI solutions. The role requires deep expertise in AI technologies, hands-on experience with machine learning frameworks, and strong proficiency in Python. Candidates should possess leadership skills and a solid understanding of cloud platforms. This is an excellent opportunity for professionals eager to drive innovative AI projects in an enterprise setting.

Qualifications

• Minimum 5 years of experience architecting and deploying AI/ML solutions.
• Deep expertise in generative AI technologies.
• Strong familiarity with MLOps practices and cloud platforms.

Responsibilities

• Architect and develop scalable GenAI pipelines and microservices.
• Lead embedding model selection and tuning for performance.
• Oversee LLM Ops workflows, including deployment and monitoring.

Skills

Architecting scalable AI solutions

Deep learning expertise

Machine learning frameworks

Cloud platforms (AWS, Azure, GCP)

Prompt engineering

Python proficiency

Education

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

Tools

TensorFlow

PyTorch

MLflow

Databricks

Azure ML

Vertex AI

Job description

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.