306 AI Engineer jobs in Singapore

POSITION OVERVIEW : AI Engineer

POSITION GENERAL DUTIES AND TASKS :

Position Summary:

We are seeking a highly skilled and experienced GenAI Engineer to join our team. The ideal candidate will have a strong background in GenAI development, with a focus on Azure and OpenAI integration. Experience with AWS and Google GenAI services is preferred. As a GenAI Engineer, you will play a key role in designing, developing, and implementing cutting-edge GenAI solutions that leverage the power of Azure and OpenAI technologies.

Role and Responsibilities:

• Design, develop, and implement GenAI solutions that integrate with Azure and OpenAI platforms.

• Collaborate with cross-functional teams to gather requirements and define project objectives.

• Conduct research and stay up-to-date with the latest advancements in GenAI, Azure, OpenAI, AWS, and Google GenAI technologies.

· Develop and maintain scalable and efficient codebase for GenAI applications. · Optimize GenAI models and algorithms for performance and accuracy.

• Troubleshoot and debug GenAI applications, ensuring smooth operation and minimal downtime.

• Collaborate with data scientists and machine learning engineers to enhance GenAI capabilities.

• Provide technical guidance and mentorship to junior team members.

• Stay informed about industry trends and best practices in GenAI engineering and cloud service integration.

Requirements:

• Bachelor's or master's degree in computer science, Engineering, or a related field.

• Proven experience as a GenAI Engineer, with a focus on Azure and OpenAI integration. Experience with AWS and Google GenAI services is preferred.

• Strong programming skills in languages such as Python and/or Java.

• Experience with Azure services, including Azure Machine Learning, Azure Cognitive Services, and Azure Functions.

Familiarity with OpenAI technologies, such as GPT-3/4 and reinforcement learning frameworks.

• Solid understanding of machine learning algorithms and deep learning frameworks.

• Proficiency in data preprocessing, feature engineering, and model evaluation techniques.

· Strong problem-solving and analytical skills. · Excellent communication and collaboration abilities.

• Ability to work independently and as part of a team in a fast-paced environment.

Preferred Qualifications:

• Experience with AWS services, such as Amazon SageMaker, AWS Lambda, and AWS AI/ML services.

• Knowledge of Google Cloud services, including Google Cloud AI Platform, Google Cloud Functions, and Google Cloud AutoML

• Experience with cloud-based deployment and scaling of GenAI applications on Azure, AWS, and Google Cloud.

• Knowledge of containerization technologies such as Docker and Kubernetes.

· Familiarity with DevOps practices and tools for CI/CD pipelines. · Contributions to open-source GenAI or cloud service integration projects

ourteam is hiring an AI Engineer on behalf of a US-based AI company building next-generation voice assistants for business travelers. In this role, you'll design retrieval-augmented generation (RAG) pipelines, engineer prompts, and fine-tune large language models to deliver natural, hands-free experiences. This role will play a key part in delivering enterprise-grade knowledge assistants and AI-driven products.

Role Description

This is a full-time role open to remote talent in Singapore or Malaysia, with hybrid options available. From prompt design to large-scale deployment, you'll help deliver voice-first AI experiences to users worldwide.

Key Responsibilities

• Design and implement intelligent applications leveraging RAG frameworks, integrating retrieval with generative models.
• Build and optimize prompt templates to improve model accuracy, consistency, and controllability.
• Evaluate and select embedding models, vector databases (e.g., FAISS, Pinecone, Milvus), and large language models.
• Develop and maintain data pipelines for knowledge bases, including document parsing, chunking, cleaning, and vectorization.
• Research and apply prompt tuning, fine-tuning, and LLMOps methods to enhance model performance.
• Monitor and analyze production performance, continuously improving accuracy and robustness.
• Collaborate closely with product managers and engineering teams to embed AI capabilities into business solutions.

Qualifications

Required

• Bachelor's degree in Computer Science, AI, Data Science, or related field
• Strong understanding of large language models (OpenAI, LLaMA, Claude, etc.)
• Proficiency in prompt engineering, with the ability to design and optimize prompts for different use cases.
• Hands-on experience with RAG systems, including vector guidelines and retrieval pipelines
• Proficiency in Python, plus frameworks like PyTorch, LangChain, LlamaIndex
• Familiarity with cloud (AWS/GCP) and containerized deployment (Docker/Kubernetes)
• Excellent problem-solving and collaboration skills

Nice-to-Have

• Experience fine-tuning LLMs or parameter-efficient tuning (LoRA, PEFT)
• Background in multimodal AI (voice, text, image)
• Experience in MLOps/LLMOps for AI pipelines
• Contributions to AI/NLP research or open source projects

What We Offer

• Competitive salary with performance-based bonuses
• Flexible remote/hybrid work setup
• Access to extensive learning resources and career development opportunities.
• Comprehensive health benefits and team-building activities

About ourteamourteam is building the future of work for Southeast Asia's AI economy. We connect fast-growing companies with top-tier talent—on-demand, vetted, and ready to go. Whether you're hiring engineers, designers, or operators, ourteam makes it simple with AI screening, instant placement, and seamless payroll integration. We're here to unlock access to world-class opportunities across the region—for individuals, teams, and companies alike.

Job Type: Full-time

Work Location: Remote

Recruitfirst is hiring You will be outsourced to:

Location: East

Working Hours:Mon- Fri, 8:30am – 6:00pm

Duration: 12 months contract

Salary: Up to $6,500 per month

Job Description:

• Manage AI Platform: Set up and oversee both development and production infrastructure for AI/ML workloads, ensuring reliability, scalability, and performance.
• Data Infrastructure: Build robust data ingest and transformation pipelines to support AI/ML model training and inference at scale.
• Model Deployment: Collaborate closely with data scientists to convert AI/ML models into deployable services using best practices in MLOps.
• System Integration: Integrate AI solutions with existing platforms and business systems through APIs, microservices, or other means.
• Access Enablement: Develop APIs or lightweight UIs to make AI capabilities easily accessible to partners and business users.
• Coordinate with different functional teams to implement models and monitor outcomes

Requirements:

• Bachelor of Computer Science/Engineering, Data Analytics & AI or other related area.
• Fluent in Python programming, Linux Systems,
• S trong background in software engineering, data engineering, or AI infrastructure
• Experience with cloud platforms (Azure) and containerization tools (Docker, Kubernetes)
• Familiarity with building RESTful APIs and/or frontend tools for AI interfaces
• Solid understanding of MLOps practices and tools (e.g., MLflow, FastAPI)
• Excellent written and verbal communication skills for coordinating across teams
• Singaporeans only

Company:

Location: Singapore

is building next-generation automation tools that generate value-based content and boost productivity across industries. We specialize in integrating frontend, backend, and AI systems into seamless products that empower enterprises and creators. With a strong commitment to AI safety and ethics , we are dedicated to responsible AI adoption that drives innovation while ensuring trust and compliance.

We are looking for an AI Engineer with hands-on expertise in Agentic AI systems, LLM-driven applications, Retrieval-Augmented Generation (RAG), and Generative AI (GenAI) . The ideal candidate will have strong foundations in end-to-end AI pipeline deployment , a passion for AI safety and responsible AI practices , and the ability to work across both system architecture and product implementation .

This role offers the opportunity to co-create automation products that sit at the intersection of AI, productivity, and scalable design .

• Agent Engineering : Design and build intelligent AI agents capable of decision-making, tool usage (APIs, code execution, databases), and multi-agent collaboration for task delegation and workflow automation.
• RAG & LLM Applications : Develop secure, enterprise-ready RAG pipelines for improving information retrieval, contextual accuracy, and scalability across content intelligence and automation use cases.
• Generative AI Development : Fine-tune transformers and integrate ControlNet, LORA, and diffusion-based models to deliver high-quality content generation across modalities.
• Product & Automation Integration : Work on both frontend (interactive user experiences) and backend (APIs, databases, pipelines) to ensure smooth product delivery.
• Knowledge Management Systems : Build context-aware knowledge agents that empower customer support, content creation, and enterprise workflows.
• AI Safety & Governance : Implement guardrails, ethical guidelines, and monitoring systems to ensure safe, reliable, and compliant AI deployments.
• Collaboration : Work with cross-functional teams on scalable deployment using cloud platforms (GCP, AWS, Azure) and workflow automation tools.

• Strong experience in Python , PyTorch , and AI frameworks such as LangChain, LangSmith, Hugging Face, and FastAPI .
• Demonstrated work on Agentic AI workflows, RAG pipelines, and GenAI solutions .
• Hands-on experience with cloud platforms (Google Cloud Platform, Vertex AI, BigQuery, Docker, Kubernetes, AWS, or Azure).
• Proficiency in vector databases, API integration, and scalable system design .
• Exposure to computer vision, NLP, and reinforcement learning is a plus.
• Strong understanding of AI safety, ethics, and responsible AI practices .
• Familiarity with workflow automation tools (e.g., Power Automate, UiPath) is desirable.
• Problem-solving mindset with the ability to translate research into production-ready solutions .

• Be part of a fast-growing company shaping the future of AI-powered productivity tools .
• Work on cutting-edge GenAI and Agentic AI systems with real-world impact.
• Opportunity to co-create open-source projects and contribute to the AI community.
• A culture that values innovation, collaboration, and responsible AI .

Responsibilities:

• Design, develop, and implement GenAI solutions that integrate with Azure and OpenAI platforms.
• Collaborate with cross-functional teams to gather requirements and define project objectives.
• Conduct research and stay up-to-date with the latest advancements in GenAI, Azure, OpenAI, AWS, and Google GenAI technologies.
• Develop and maintain scalable and efficient codebase for GenAI applications. · Optimize GenAI models and algorithms for performance and accuracy.
• Troubleshoot and debug GenAI applications, ensuring smooth operation and minimal downtime.
• Collaborate with data scientists and machine learning engineers to enhance GenAI capabilities.
• Provide technical guidance and mentorship to junior team members.
• Stay informed about industry trends and best practices in GenAI engineering and cloud service integration.

Requirements:

• Bachelor's or master's degree in computer science, Engineering, or a related field.
• Proven experience as a GenAI Engineer, with a focus on Azure and OpenAI integration. Experience with AWS and Google GenAI services is preferred.
• Strong programming skills in languages such as Python and/or Java.
• Experience with Azure services, including Azure Machine Learning, Azure Cognitive Services, and Azure Functions.
• Familiarity with OpenAI technologies, such as GPT-3/4 and reinforcement learning frameworks.
• Solid understanding of machine learning algorithms and deep learning frameworks.
• Proficiency in data preprocessing, feature engineering, and model evaluation techniques.
• Strong problem-solving and analytical skills. · Excellent communication and collaboration abilities.
• Ability to work independently and as part of a team in a fast-paced environment.
• Experience with AWS services, such as Amazon SageMaker, AWS Lambda, and AWS AI/ML services.
• Knowledge of Google Cloud services, including Google Cloud AI Platform, Google Cloud Functions, and Google Cloud AutoML
• Experience with cloud-based deployment and scaling of GenAI applications on Azure, AWS, and Google Cloud.
• Knowledge of containerization technologies such as Docker and Kubernetes.
• Familiarity with DevOps practices and tools for CI/CD pipelines. · Contributions to open-source GenAI or cloud service integration projects

Responsibilities

• Translating business needs into AI agent solutions.
• Rapid prototyping of new ideas and evaluate performance.
• Building scalable, production-ready agent architectures.
• Designing and building AI agents (customer service bots, workflow automation, decision-support systems).
• Integrating LLMs (OpenAI, Anthropic, Meta LLaMA) with APIs, databases, and internal systems.
• Implementing reasoning, planning, memory, and tool-use capabilities in agents.
• Optimizing performance, latency, and reliability.
• Performing model updates, prompt refinements, and minor enhancements under guidance.
• Ensuring AI workflows and integrations (Microsoft 365, Power Platform) run smoothly.
• Troubleshooting and resolving technical issues.
• Documenting systems and AI workflows, updates, and best practices for internal teams.
• Training internal teams to adopt AI tools.
• Training and assisting AI applications built on Azure OpenAI, Cognitive Search, and Semantic Kernel.
• Tracking usage, costs, and performance metrics, providing insights for optimization.
  Staying up to date with the latest developments in Generative AI and Microsoft AI tools as well as state-of-the-art agent frameworks (LangChain, AutoGPT, CrewAI, Semantic Kernel, etc.); applying them to improve existing solutions.

Requirements

• 3 years in Python programming.
• Exposed to ML frameworks (PyTorch, Hugging Face, or scikit-learn).
• Knowledge of Microsoft Azure AI stack (Azure OpenAI, Cognitive Search, Azure Machine Learning).
• Knowledge of of REST APIs and system integration.
• Able to communicate across both technical and non-technical stakeholders.
• Advantages to have
• LLM applications, RAG pipelines, or prompt engineering.
• Microsoft Power Platform (Power BI, Power Automate).
  Responsible AI practices (fairness, bias, compliance).

Ethos Search Associates Pte. Ltd.

EA License No: 13C6655

EA Reg No: R Jacky Chong

You'll become a core developer who directly designs and implements AI Agents that transform the paradigm of education. You'll experience the entire AI development lifecycle from prototype stage to actual operational systems, building innovative AI algorithms that automatically generate hands-on exercises, projects, and quizzes. Through advancing RAG (Retrieval-Augmented Generation) frameworks, you'll enhance AI's contextual understanding capabilities and pursue the challenging goal of achieving TRL 9 level technology readiness. Seize the opportunity to gain practical experience with cutting-edge LLM technology and conversational systems while growing as an AI expert in the global EdTech field

• AI Agent System Development Lead the entire development process from EdTech AI Agent prototype to actual operational system

Design, implement, and optimize Core AI Agentic System

Validate AI systems in real operational environments through collaboration with pilot institutions
- Educational Content Generation AI Development Build and advance AI algorithms for automatic generation of AI exercises, projects, and quizzes

Fine-tune AI models optimized for educational contexts and improve performance

Develop educational AI solutions utilizing large language models and code datasets
- RAG System Enhancement Improve RAG Framework performance and enhance AI Model contextual relevance within the system

Identify latest AI technology trends through research papers and apply them to practical work

Improve AI system efficiency through data analysis and processing optimization

• Must reside in Singapore
• Proficiency in AI/ML model development and fine-tuning
• Experience implementing LLM and RAG systems
• Bachelor's degree or higher in AI and machine learning fields, or equivalent experience
• Knowledge of data analysis and processing
• Experience with large language models, conversational systems, and code datasets
• Research paper reading comprehension ability

• Ability to enhance work efficiency and optimize performance using AI tools

• Preferred Qualifications

• Experience with AI projects in EdTech or educational technology fields

• Experience deploying AI models in cloud environments

COMPANY DESCRIPTION

Mediacorp is Singapore's largest content creator and national media network, operating a suite of TV channels, radio stations, and multiple digital platforms. Its mission is to engage, entertain, and enrich audiences by harnessing the power of creativity.

We are committed to creating an inclusive and diverse workplace where talent thrives. Our hiring decisions are made based on merit and fit-to-role. If you have a disability or special need which requires accommodation to participate in the recruitment process, please inform us when you submit your online application. We will be happy to support as necessary.

Thank you for your interest and application to this role. Please note that only short-listed candidates will be contacted.

RESPONSIBILITIES

We are seeking a highly skilled and motivated AI Engineer to join our team. This role is ideal for professionals who excel in developing and deploying AI-powered applications, integrating machine learning models into scalable systems, and architecting robust, end-to-end solutions. The successful candidate will work at the intersection of AI/ML development, full-stack engineering, and system architecture, driving innovation and delivering impactful solutions.

Responsibilities:

AI/ML Development:

• Design, develop, and deploy generative AI and machine learning models for diverse use cases e.g. LLM, text-to-speech, image generation.
• Perform data preprocessing, feature engineering, and model optimization.
• Implement and fine-tune AI/ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.
• Develop APIs to expose AI models for seamless integration into applications.
• Stay updated on advancements in generative AI research and tools to maintain cutting-edge implementations.

Deployment and Operations:

• Deploy AI models and applications using modern DevOps and MLOps practices.
• Containerize applications using Docker and orchestrate deployments with Kubernetes.
• Set up CI/CD pipelines for seamless code and model delivery.
• Monitor application performance and ensure high availability in production environments.

System Design and Architecting:

• Architect scalable, modular, and efficient application systems that integrate AI/ML models.
• Design end-to-end pipelines for data ingestion, processing, model serving, and monitoring.
• Ensure system designs adhere to best practices for security, compliance, and reliability.

Collaboration and Leadership:

• Work closely with data scientists, software engineers, and product teams to align AI solutions with business objectives.
• Provide technical leadership and mentorship to junior team members.
• Collaborate with stakeholders to identify opportunities and requirements for AI-driven solutions.

QUALIFICATIONS

• Bachelor's or master's degree in computer science, Engineering, or a related field.
• 5+ years of developing end-to-end AI/ML applications.
• Strong programming in at least one of the following languages: Python, Scala, JavaScript.
• Experience with AI/ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn, OpenAI).
• Expertise in system design and application architecture.
• Familiarity with databases (SQL/NoSQL) and data pipelines.
• Experience with cloud platforms (AWS, Azure, GCP) and containerization tools (Docker, Kubernetes).
• Solid understanding of DevOps/MLOps practices.
• Experience deploying and managing AI solutions in production environments is preferred.
• Hands-on experience with fine-tuning generative AI models for specific business applications is preferred.
• Knowledge of microservices architecture and serverless computing is preferred.
• Proficiency in front-end frameworks (e.g., React, Angular) and back-end development is preferred.
• Familiarity with monitoring tools (e.g., Prometheus, Grafana) and logging frameworks is preferred.

Please note that your application will be sent to and reviewed by the direct employer - Mediacorp Pte. Ltd.

Company Summary :

ELGO AI is a fast-growing startup redefining how enterprises build and deploy AI. We offer a powerful no-code enterprise-grade GenAI platform that enables organizations to create custom LLM-powered applications such as chatbots, smart document workflows, and automation agents 10x faster than traditional methods. Abstracting away the complexities of a production GenAI system, we aim to simplify enterprise AI adoption by making advanced GenAI capabilities accessible to non-technical teams. We are passionate about workflow orchestration, context-aware agents, full transparency and observability layer, scalable designs and enterprise-grade deployment, all grounded in responsible, secure, and user-centric design. Our vision is to become the go-to operating platform for practical AI solutions in Asia Pacific.

Job Description:

As an AI Engineer, you'll play a key role in the development and optimization of ELGO's no-code platform and LLM-based workflows. Instead of model training or fine-tuning, your focus will be on building reusable, configurable, and scalable LLM-powered components and highly optimized task agents that can be orchestrated by users without writing code. We also constantly push the frontiers on LLM techniques and designs to ensure that our agents are state-of-the-art.

You'll work closely with our CTO and engineering team to implement advanced LLM workflows, multi-agent logic, evaluation mechanisms, and performance monitoring that power real-world business applications.

The ideal person for the role would love the fast-changing and dynamic environment, working with new technologies and translating that into real world impact. He/she would also enjoy the opportunity to work on multiple real-world LLM systems, and constantly push him/herself to be better. He/she is would also be extremely proactive, both in working and learning.

Caution: this is likely going to be the toughest role ever you would have in your life, but it could also be the most rewarding.

Roles & Responsibilities:

• Develop and optimize backend systems for LLM workflow orchestration (retrieval, chaining, evaluation, memory, task-based agent optimizations).

• Implement reusable components (e.g., retrieval nodes, validation agents, evaluators) to power the no-code platform.

• Integrate and manage third-party models (e.g., OpenAI, Anthropic, AWS Bedrock, open-source models).

• Develop and maintain multi-agent and tool-augmented AI workflows for common enterprise use cases.

• Work on document processing, cross-system integrations, RAG pipelines, contextual memory management, and prompt engineering best practices.

• Research and development new techniques to tackle the toughest problems in LLM applications.

• Collaborate with front-end and platform engineers to support the no-code interface.

• Conduct systematic evaluations and performance tracking of LLM applications in production.

• Stay updated with emerging GenAI and agentic framework trends.

Requirements:

Core Requirements

• Bachelor's degree in Computer Science, AI/ML Engineering, or equivalent experience with about 2-4 years relevant working experience. Candidates without formal education but with strong practical experience are welcomed.

• Strong Python programming skills with experience in).

• Experience in building production-grade RAG applications and integrating with APIs.

• Familiarity with databases (e.g., PostgreSQL, MongoDB, Redis).

• Foundational programming knowledge (Git, Docker, OOP, FastAPI).

• Understanding of LLM architecture and practical applications.

Key Traits

• Strong problem-solving and systems thinking.

• Bias for action and comfort working in a fast-paced startup environment.

• Clear communication and collaborative mindset.

• Curiosity and openness to new ideas and technologies.

• Willingness to contribute beyond code – including product feedback, customer empathy, and roadmap planning.

Optional Requirements

• Familiarity with vector databases (e.g., Qdrant, Weaviate, Pinecone etc.).

• Experience building agentic workflows or using any frameworks like LangChain, Langgraph, CrewAI, AutoGen, Vercel SDK, OpenAI Agents SDK etc.

• Good understanding about transformers, LLMs, multi-agent systems, tool uses/function calling.

• Prior work with evaluation frameworks for LLM performance and safety.

What We Offer:

• A front-row seat to building the next generation of enterprise GenAI tooling and real-world applications.

• The opportunity to be part of a small but elite team of Asia's most promising GenAI startups.

• Exposure to real-world challenges and impactful deployments.

• A supportive and transparent team environment that values outcomes over hours. No politics, full focus on solving real problems.

• Growth opportunities across product, engineering, AI and R&D.

The Interview Process:

• There will be a total of 3 rounds of interview:

o 1st round: 30 minutes of general Q&A with the CEO

o 2nd round: 60 minutes technical session, where you will be given a real problem and is required to code out the solution within 30 minutes. Technical Q&A for the remaining time.

o 3rd round: 15 minutes for work arrangements and compensation package discussions.