AI Engineer (Software Development Engineer)

AMD; Singapore; On-site; SGD 70,000 - 120,000; Full time

Job summary

AMD is seeking an AI Engineer to join its AI Engineering team, focused on Agentic AI and Digital Workers. You will participate in the lifecycle from prompt engineering to deploying AI agents in business environments, collaborating with senior engineers and stakeholders to automate workflows and boost enterprise productivity.

This role targets early-career engineers excited about LLMs, AI agents, and enterprise AI deployment, offering mentorship and growth opportunities.

Qualifications

• Strong Python programming skills.
• Understanding of APIs, JSON, REST services, and software integration.
• Familiarity with machine learning and natural language processing fundamentals.
• Strong analytical and structured problem-solving abilities.
• Ability to learn quickly in a fast-paced and evolving AI environment.
• Strong communication and collaboration skills.
• OpenAI, Azure OpenAI, Anthropic, Google Gemini, or similar LLM platforms.
• Building LLM applications, chatbots, copilots, or AI assistants.
• Retrieval-Augmented Generation (RAG) architectures.
• Vector databases such as Pinecone, Weaviate, Chroma, Milvus, or Azure AI Search.
• LangChain, LangGraph, CrewAI, LlamaIndex, AutoGen, or Semantic Kernel.
• Function calling, embeddings, semantic search, and context management.
• Prompt engineering and AI evaluation methodologies.
• Cloud platforms such as Azure, AWS, or Google Cloud.
• Docker, Kubernetes, CI/CD pipelines, or DevOps practices.
• Git, software testing, and modern development workflows.
• Curious and passionate about AI innovation.
• Strong ownership mentality with a willingness to experiment.
• Customer-focused mindset and ability to work directly with users.
• Comfortable navigating ambiguity and solving complex problems.
• Team player who thrives in a collaborative environment.
• Eager to build AI systems that deliver measurable business impact.

Responsibilities

• Design, develop, and test AI agents capable of multi-step reasoning and workflow execution.
• Build solutions leveraging LLMs, tool usage, memory, and agent orchestration frameworks.
• Implement function calling, structured outputs, and automated workflows.
• Develop Retrieval-Augmented Generation (RAG) pipelines using enterprise knowledge sources.
• Optimize AI system performance, reliability, scalability, and response quality.
• Assist in evaluating and benchmarking AI model effectiveness.

Skills

Python

APIs & JSON

ML/NLP fundamentals

Analytical thinking

Communication

Learning agility

Problem solving

Team collaboration

Education

Degree in Computer Science and Art

Tools

OpenAI / Azure OpenAI

Anthropic

Google Gemini

LangChain

LlamaIndex

RAG architectures

Pinecone

Weaviate

Chroma

Milvus

Azure AI Search

Docker

Kubernetes

CI/CD

Git

Job description

ADVANCE YOUR CAREER. ADVANCE THE WORLD.

At AMD, we believe technology has the power to solve the world's most important challenges. From advancing healthcare and scientific discovery to powering AI and the technologies people rely on every day, innovation at AMD is shaping the future.

Whether you're designing next-gen processors, enabling AI breakthroughs, or bringing leading edge products to market, every role at AMD contributes to something bigger - technology that moves the world forward. Join us and, together, we'll advance your career.

THE ROLE:

We are seeking a passionate and highly motivated AI Engineer to join our AI Engineering team focused on building the next generation of Agentic AI and Digital Workers .

In this role, you will participate in the complete lifecycle of AI solution development, from prompt engineering and context engineering to deploying AI agents into real business environments. You will work alongside senior AI engineers, business stakeholders, and domain experts to build intelligent systems that automate workflows, enhance productivity, and transform enterprise operations.

This is an excellent opportunity for early-career engineers who are excited about Large Language Models (LLMs), AI agents, Retrieval-Augmented Generation (RAG), and enterprise AI deployment.

THE PERSON:

WHAT YOU WILL GAIN

• Hands-on experience building real-world Agentic AI systems


• Exposure to enterprise-scale AI deployment and Digital Worker platforms


• Mentorship from experienced AI engineers and architects


• Opportunities to work with cutting-edge LLM technologies and AI frameworks


• Direct involvement in AI transformation initiatives across multiple business functions


• Career growth path toward AI Engineer, Senior AI Engineer, AI Architect, or Forward Deployment Engineer roles

KEY RESPONSIBILITIES:

Agentic AI Development

• Design, develop, and test AI agents capable of multi-step reasoning and workflow execution


• Build solutions leveraging LLMs, tool usage, memory, and agent orchestration frameworks


• Implement function calling, structured outputs, and automated workflows


• Develop Retrieval-Augmented Generation (RAG) pipelines using enterprise knowledge sources


• Optimize AI system performance, reliability, scalability, and response quality


• Assist in evaluating and benchmarking AI model effectiveness

Prompt & Context Engineering

• Design effective system prompts and task-specific prompts


• Build context retrieval and grounding strategies to improve AI accuracy


• Develop methods to reduce hallucinations and improve consistency


• Support the creation of evaluation frameworks and automated testing pipelines


• Experiment with prompting techniques, reasoning patterns, and agent behaviors

Forward Deployment Engineering (FDE)

• Deploy AI solutions into real business processes and operational environments


• Integrate AI agents with APIs, databases, enterprise platforms, and business applications


• Collaborate directly with stakeholders to understand requirements and refine use cases


• Monitor deployed systems, troubleshoot issues, and implement enhancements


• Gather feedback and continuously improve AI solutions based on business outcomes

Software Engineering & Operations

• Develop and maintain production-quality Python applications


• Implement logging, monitoring, testing, and observability practices


• Participate in code reviews and engineering best practices


• Support cloud deployment and containerized AI environments


• Document technical solutions and operational procedures

PREFERRED EXPERIENCE

• Strong Python programming skills


• Understanding of APIs, JSON, REST services, and software integration


• Familiarity with machine learning and natural language processing fundamentals


• Strong analytical and structured problem-solving abilities


• Ability to learn quickly in a fast-paced and evolving AI environment


• Strong communication and collaboration skills


• OpenAI, Azure OpenAI, Anthropic, Google Gemini, or similar LLM platforms


• Building LLM applications, chatbots, copilots, or AI assistants


• Retrieval-Augmented Generation (RAG) architectures


• Vector databases such as Pinecone, Weaviate, Chroma, Milvus, or Azure AI Search


• Agent frameworks including LangChain, LangGraph, CrewAI, LlamaIndex, AutoGen, or Semantic Kernel


• Function calling, embeddings, semantic search, and context management


• Prompt engineering and AI evaluation methodologies


• Cloud platforms such as Azure, AWS, or Google Cloud


• Docker, Kubernetes, CI/CD pipelines, or DevOps practices


• Git, software testing, and modern development workflows


• Curious and passionate about AI innovation


• Strong ownership mentality with a willingness to experiment


• Customer-focused mindset and ability to work directly with users


• Comfortable navigating ambiguity and solving complex problems


• Team player who thrives in a collaborative environment


• Eager to build AI systems that deliver measurable business impact

ACADEMIC CREDENTIALS:

Degree in Computer Science, Art