Snr Principal AI Engineer - Software

ST ENGINEERING IHQ PTE. LTD.; Singapore; On-site; SGD 75,000 - 105,000; Full time

Job summary

A technology company in Singapore is seeking a Mid-to-Senior Software Engineer to build a Computer Vision platform using AI agents. This hands-on role involves designing scalable systems, API development, and managing the software lifecycle. Ideal candidates have over 8 years of experience in software engineering and a strong background in AI/ML systems. A 2-year contract position offers the chance to innovate within a cutting-edge environment.

Qualifications

• 8+ years of hands-on software engineering experience.
• 2-3 years building AI/ML systems.
• Strong understanding of Computer Vision workflows.

Responsibilities

• Design and implement scalable agent-driven systems.
• Develop APIs and backend services for agent orchestration.
• Own the end-to-end software lifecycle.

Skills

Python development

AI/ML systems

CI/CD pipelines

Containerization (Docker, Kubernetes)

Cloud infrastructure (AWS, GCP, Azure)

API development

Database technologies (SQL/NoSQL)

Computer Vision workflows

Tools

FastAPI

Flask

PyTorch

TensorFlow

Job description

We’re building the next generation of computer vision development—where AI agents automate data curation, model tuning, and deployment, accelerating the delivery of real-world AI systems. Our mission is to bridge cutting-edge research with production software by empowering engineers with intelligent tools that scale. As part of our team, you’ll help build the infrastructure and systems that make this future possible. We work closely with top universities and research labs, turning state-of-the-art AI ideas into deployable, high-performance solutions.

About the Role

We are looking for a Mid-to-Senior Software Engineer with strong AI/ML experience to help us design, build, and ship a Computer Vision platform powered by AI agents. You will play a key role in delivering scalable, production-grade systems that automate and accelerate ML workflows—driving model deployment, evaluation, and data pipelines. This is a hands-on role where software craftsmanship and AI expertise meet to push the boundaries of automation in computer vision.

This is a 2-year contract position (convertible if good performance) based in Singapore.

Key Responsibilities

· Design and implement scalable agent-driven systems to automate Computer Vision MLOps workflows (training, deployment, evaluation)

· Develop robust APIs and backend services that enable agent orchestration, memory management, and cross-component communication

· Integrate vector databases, data quality validation, and semantic search to power intelligent agent behavior

· Own the end-to-end software lifecycle: from development to testing, CI/CD automation, and cloud deployment

· Build for reliability and maintainability: logging, monitoring, and exception handling are part of your design thinking

· Optimize performance and cost in storage and compute, especially for vision-specific workloads

· Work with researchers and domain experts to translate state-of-the-art ideas into working code

Must-Have Skills

· 8+ years of hands-on software engineering experience, with at least 2–3 years building AI/ML systems

· Strong Python development skills, including writing testable, production-grade code

· Proven experience with:

o Designing and deploying CI/CD pipelines for ML systems

o Containerization and orchestration (Docker, Kubernetes)

o Cloud infrastructure (AWS, GCP, or Azure)

o API development using frameworks like FastAPI or Flask

o Database technologies: SQL/NoSQL and vector databases (e.g., FAISS, Weaviate)

· Familiarity with AI agent frameworks such as LangChain, AutoGen, CrewAI

· Solid understanding of Computer Vision workflows, including image classification, detection, and tracking

· Comfortable with software engineering best practices: version control, code reviews, documentation, modular design

Nice-to-Have Skills

· Demonstrated experience through personal projects, prototypes, or open-source contributions in AI, CV, or agents

· Hands-on with ML frameworks like PyTorch or TensorFlow

· Exposure to ML observability and performance monitoring tools (e.g., Grafana, Datadog, Prometheus)

· Experience building simple user-facing interfaces for demos or internal tools (e.g., with Gradio or Streamlit)

· Familiarity with unit testing frameworks (e.g., Pytest) and static analysis tools

· Prior experience in cross-functional collaboration, especially with researchers or product engineers

· Knowledge of LLM integration for autonomous agent systems