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Salary
$51k – $56k per year (gross)
Location
In office (Singapore)
Seniority
Junior
Employment
Full-Time

First seen by Alion on Oct 19, 2026.

Overview
Company
Impact
Profile match
Xilinx was a maker of programmable logic devices, including FPGAs, and is now part of AMD. Its chips and adaptive computing products are developed and supported within AMD, which lists security and engineering roles for the former Xilinx organization. The company is based in the United States.

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

Skills

Chatbot, Natural Language Understanding, Ai, JSON, Design, Scalability, Pipelines, Interpersonal Skills, Azure OpenAI, Tool Design, OpenAI Codex, AI Evaluation, Analytical and Problem-Solving Skills, Rest Apis, Programming, Workflow Solutions

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