AI Prototyper & AIOps Engineer

Tech Aalto Pte ltd

Singapore

On-site

SGD 120,000 - 160,000

Full time

11 days ago
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Job summary

Tech Aalto Pte Ltd is seeking an AI Prototyper & AIOps Engineer to rapidly test ideas, build proof-of-concepts, and operationalize AI models across diverse environments.

You will work with LLMs, RAG pipelines, and multimodal models, designing cloud-native architectures and end-to-end AIOps pipelines. You’ll help define deployment standards, security, monitoring, and continuous improvement while collaborating with PMs, architects, and engineers to turn innovation into reliable solutions.

Qualifications

  • Bachelor’s degree in CS, Engineering, or related.
  • 5+ years in ML Engineering, AIOps, or similar applied AI functions.
  • Strong Python, Docker, Kubernetes, CI/CD, and cloud experience.
  • Familiarity with LLMs, open-source models, vector DBs, and RAG.
  • Strong ability to prototype quickly and work with ambiguity.
  • Experience integrating data sources at scale.

Responsibilities

  • Build rapid prototypes using LLMs, RAG, embeddings, and multimodal models.
  • Design and implement end-to-end AIOps pipelines for training and deployment.
  • Stand up cloud infrastructure in GCP/Azure for scalable AI workloads.
  • Integrate structured, unstructured, and telemetry-style data into models.
  • Implement monitoring, observability, and automated evaluation systems.
  • Collaborate with PMs, architects, and engineers to define feasibility.
  • Produce technical documentation and contribute to delivery frameworks.
  • Experiment with new AI techniques and translate innovation into action.

Skills

Python
AIOps
ML Engineering
Prototyping
Cloud experience
Data integration
LLMs familiarity

Education

Bachelor’s degree in CS/Engineering

Tools

Docker
Kubernetes
CI/CD
GCP
Azure
Vector databases

Job description

AI Prototyper & AIOps Engineer – Applied AI Systems

If you’re driven by the challenge of rapidly prototyping AI ideas, architecting scalable pipelines, and bringing cutting-edge models into real workflows, this is your place. We’re searching for an AI Prototyper & AIOps Engineer with a rare combination of creativity, hands-on technical depth, and systems thinking. In this role, you’ll turn concepts into running prototypes, design the infrastructure that powers them, and help shape the next generation of applied AI solutions for our clients.

Description

As an AI Prototyper & AIOps Engineer, you will rapidly test ideas, build proof-of-concepts, and operationalize AI models across diverse environments. You will work across LLMs, RAG pipelines, multimodal models, forecasting systems, and cloud-native architectures. You will help define standards for model deployment, security, monitoring, and continuous improvement ensuring reliability and scalability.

Key Responsibilities
  • Build rapid prototypes using LLMs, RAG, embeddings, and multimodal models.
  • Design and implement end-to-end AIOps pipelines for training and deployment.
  • Stand up cloud infrastructure in GCP/Azure for scalable AI workloads.
  • Integrate structured, unstructured, and telemetry-style data into models.
  • Implement monitoring, observability, and automated evaluation systems.
  • Collaborate with PMs, architects, and engineers to define feasibility.
  • Produce technical documentation and contribute to delivery frameworks.
  • Experiment with new AI techniques and translate innovation into action.
Minimum Qualifications
  • Bachelor’s degree in CS, Engineering, or related.
  • 5+ years in ML Engineering, AIOps, or similar applied AI functions.
  • Strong Python, Docker, Kubernetes, CI/CD, and cloud experience.
  • Familiarity with LLMs, open-source models, vector DBs, and RAG.
  • Strong ability to prototype quickly and work with ambiguity.
  • Experience integrating data sources at scale.
Preferred Qualifications
  • Experience with MLOps/AIOps observability systems.
  • Prior consulting or customer-facing delivery experience.
  • Experience with MLX or Apple Silicon optimization workflows.
  • Passion for applied AI, experimentation, and rapid iteration.

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