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, Artificial Intelligence, Software Engineering, Data Science, or a related technical field
LOCATION
Singapore
#LI-CC6
#LI-D&I
Benefits offered are described: AMD benefits at a glance.
AMD does not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services. AMD and its subsidiaries are equal opportunity, inclusive employers and will consider all applicants without regard to age, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third-party affiliation, sex, pregnancy, sexual orientation, gender identity, military or veteran status, or any other characteristic protected by law. We encourage applications from all qualified candidates and will accommodate applicants’ needs under the respective laws throughout all stages of the recruitment and selection process.
AMD may use Artificial Intelligence to help screen, assess or select applicants for this position. AMD’s “Responsible AI Policy” is available here.
This posting is for an existing vacancy.
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 Agents. 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
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, Artificial Intelligence, Software Engineering, Data Science, or a related technical field
LOCATION
Singapore
#LI-CC6
#LI-D&I
Benefits offered are described: AMD benefits at a glance.
AMD does not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services. AMD and its subsidiaries are equal opportunity, inclusive employers and will consider all applicants without regard to age, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third-party affiliation, sex, pregnancy, sexual orientation, gender identity, military or veteran status, or any other characteristic protected by law. We encourage applications from all qualified candidates and will accommodate applicants’ needs under the respective laws throughout all stages of the recruitment and selection process.
AMD may use Artificial Intelligence to help screen, assess or select applicants for this position. AMD’s “Responsible AI Policy” is available here.
This posting is for an existing vacancy.
