Lead AI Architect

ELLIOTT MOSS CONSULTING PTE. LTD.; Singapore; On-site; SGD 120,000 - 160,000; Full time

Job summary

An innovative consulting firm in Singapore is seeking a Lead AI Architect to spearhead the design and optimization of enterprise-grade AI solutions. The ideal candidate has over 10 years of IT development experience, including 5 years in AI implementation, with strong skills in Python, cloud services, and MLOps tools. This role involves leading teams to deliver robust AI architectures and ensuring projects align with security and governance principles. Competitive compensation package offered, embracing a culture of innovation.

Qualifications

• 10+ years of IT development experience, including 5+ years implementing AI solutions.
• Proven experience contributing to or leading large-scale AI or data initiatives.

Responsibilities

• Design and implement scalable AI architectures and LLM pipelines.
• Build, deploy, and optimise AI/ML and GenAI applications.

Skills

Python programming

AI/ML frameworks (PyTorch, TensorFlow)

LLM frameworks and libraries (Transformers, LangChain, LlamaIndex)

RAG workflows, embeddings, and vector databases (Pinecone, Milvus, Weaviate)

Cloud AI services

Containerization (Docker)

Kubernetes

Serverless architectures

MLOps / GenAIOps tools (MLflow, Vertex AI, SageMaker, Databricks)

Data engineering

API development

Observability

Education

Bachelor’s degree in Computer Science, Information Systems, or a related field

Master’s degree in a related field

Job description

Job Description

• As a Lead AI Architect (Principal IT Architect), you will be responsible for building, deploying, and optimizing enterprise-grade AI/ML and Generative AI solutions.
• This role leads the design and implementation of scalable AI architectures, LLM pipelines, and data platforms, while working closely with architects, engineering, and product teams to deliver production-ready, secure, and high-performing AI systems.
• What will you do? Enterprise AI Architecture & Strategy Design, define, and maintain the organisation’s enterprise.
• AI architecture and standards Ensure AI solutions align with overall IT architecture, security, and governance principles.
• Lead the team to ensure designs and code conform to approved architecture and standards AI/ML & GenAI Solution.
• Delivery Build, deploy, and optimise AI/ML and GenAI applications Implement LLM pipelines, RAG workflows, retrieval strategies, and vector database integrations.
• Fine-tune, evaluate, and optimise LLMs for latency, accuracy, cost, and safety Data & Model Engineering Build data ingestion, feature engineering, and model training pipelines Implement embeddings, retrieval optimisation, and model evaluation techniques.
• Ensure AI solutions meet data quality, performance, and scalability requirements Platform, MLOps & Observability Develop APIs, microservices, and automation supporting AI capabilities Implement monitoring, logging, prompt evaluation, and automated testing for AI systems.
• Apply MLOps / GenAIOps practices for model lifecycle management.
• Collaboration & Quality Assurance Collaborate with architects, engineers, and product teams to deliver production-ready.
• AI solutions Participate in peer reviews to improve solution quality, performance, and maintainability.

Qualifications

• 10+ years of IT development experience, including 5+ years implementing AI solutions.
• Strong Python programming skills with AI/ML frameworks (PyTorch, TensorFlow)
• Hands-on experience with LLM frameworks and libraries (Transformers, LangChain, LlamaIndex)
• Experience implementing RAG workflows, embeddings, and vector databases (Pinecone, Milvus, Weaviate)
• Experience with cloud AI services, containerisation (Docker), Kubernetes, and serverless architectures.
• Familiarity with MLOps / GenAIOps tools (MLflow, Vertex AI, SageMaker, Databricks)
• Strong grounding in data engineering, API development, and observability.
• Understanding of responsible AI, prompt engineering, evaluation, and data governance frameworks.
• Proven experience contributing to or leading large-scale AI or data initiatives.
• Bachelor’s degree in Computer Science, Information Systems, or a related field Master’s degree in a related field (preferred).