AI Engineer

FLARE CONSULTING PTE. LTD.; Singapore; On-site; SGD 80,000 - 120,000; Full time

Job summary

A technology consulting firm is seeking an AI Software Engineer in Singapore to develop scalable AI systems leveraging Azure technologies. The role involves end-to-end AI solution development, backend service creation using FastAPI, and managing data pipelines. Candidates should have strong programming skills in FastAPI, experience with Azure cloud fundamentals, and a solid foundation in AI/ML algorithms. The position offers a competitive salary and a chance to work on innovative projects in a collaborative team environment.

Benefits

Competitive salary

Comprehensive benefits package

Access to state-of-the-art technology

A culture valuing innovation and growth

Qualifications

• Strong programming skills and experience with FastAPI.
• Hands-on with Azure Cloud fundamentals.
• Experience in GitLab CI/CD pipelines.
• Familiarity with Ansible and REX for deployments.
• Knowledge of Prompt Engineering and software testing.
• Experience in data pipeline development.
• Foundational knowledge of AI/ML algorithms.
• Experience with Azure ML deployment.

Responsibilities

• Design, build, and deploy scalable AI models and systems.
• Develop backend services using FastAPI and integrate AI capabilities.
• Utilize Azure Cloud services for model deployment.
• Build and monitor efficient data pipelines.
• Apply expert knowledge in Prompt Engineering and OpenAI models.
• Continuously optimize AI models for performance.

Skills

Strong programming skills with FastAPI

Hands-on experience with Azure Cloud fundamentals

Practical knowledge of GitLab CI/CD pipelines

Experience with deployment tools like Ansible

Solid understanding of Prompt Engineering

Data pipeline development

Knowledge of AI/ML algorithms

Experience with Azure ML

Tools

Azure ML

GitLab

TensorFlow

FastAPI

Ansible

REX

Job description

About the Role

We are seeking a highly skilled AI Software Engineer to join our innovative team. In this role, you will be at the forefront of designing, building, and deploying scalable AI systems and models. You will leverage cutting‑edge technologies, including the Azure OpenAI ecosystem, to solve complex problems and deliver intelligent solutions that have a direct business impact. This is a hands‑on role that blends software engineering, data science, and MLOps.

Key Responsibilities

• End-to-End AI Solution Development: Design, build, and deploy robust and scalable AI models and systems from concept to production.
• API & Application Development: Develop and maintain backend services using FastAPI and integrate AI capabilities into user-facing applications.
• Cloud & MLOps Engineering: Utilize Azure Cloud services (including Azure ML and Azure AI Search) to build, train, and deploy models. Implement and manage CI/CD pipelines using GitLab and Ansible/REX for automated testing and deployment.
• Data Pipeline & Management: Build and monitor efficient data pipelines for model training and inference. Work with various data storage solutions like Azure Storage, PostgreSQL, and Cosmos DB.
• Advanced AI & NLP: Apply expert knowledge in Prompt Engineering and the OpenAI GPT family of models (including GPT-4o) to develop sophisticated applications. Implement embeddings and vector search for advanced retrieval systems.
• Model Optimization & Evaluation: Continuously optimize AI models for performance, latency, and scalability. Conduct rigorous model evaluation and validation.
• Collaboration & Best Practices: Work collaboratively within cross‑functional teams, adhering to software engineering principles (version control, CI/CD, containerization) and modern testing standards.

Key Performance Indicators (KPIs)

Your success will be measured by your ability to:

• Deployment Velocity: Reduce the time-to-production for new AI models and features.
• System Reliability & Performance: Maintain high uptime for AI services and ensure models meet predefined latency and throughput targets.
• Model Efficacy: Achieve and maintain key metrics for model accuracy, precision, and recall in production.
• Pipeline Efficiency: Improve the stability and monitoring coverage of data and MLOps pipelines, reducing failure rates.
• Business Impact: Demonstrate the value of deployed AI solutions through measurable business outcomes.

Skills & Qualifications

Required (Proficient):

• Strong programming skills with experience in FastAPI.
• Hands‑on experience with Azure Cloud fundamentals and Azure DevOps.
• Practical knowledge of building and maintaining GitLab CI/CD pipelines.
• Experience with deployment and configuration tools like Ansible and REX.
• Solid understanding of Prompt Engineering and modern software testing practices.
• Proven ability in data pipeline development and monitoring.
• Strong foundational knowledge of AI/ML algorithms and MLOps frameworks.
• Experience with Azure ML and the model deployment lifecycle.

Preferred (Expert):

• Expertise in the Azure OpenAI ecosystem and the GPT family of models.
• Deep experience with embeddings and vector search technologies, preferably with Azure AI Search.
• Proficiency with ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.
• Experience with other cloud AI platforms (e.g., AWS SageMaker, Google AI Platform).
• Expertise in data preprocessing, feature engineering, and model evaluation.
• Strong familiarity with distributed computing tools like Spark or Hadoop.
• Proven ability to optimize models for performance and scalability.

What We Offer

• A competitive salary and comprehensive benefits package.
• The opportunity to work with a talented team on challenging, green‑field projects.
• Access to state‑of‑the‑art technology and tools.
• A culture that values innovation, continuous learning, and professional growth.