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Unison GroupSingapore, Singapore

AI Engineer - Forward Deployed Engineer

Posted 3mo agoML & AI Engineer

At a glance

Posted
16 July 2026
Type
Full-time
Level
Mid level
Country
Singapore
Skills named
aws, azure, containers, docker, kubernetes, langchain, llamaindex, llm
Application form
Workable

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About the Role

We are looking for an experienced

AI Engineer (FDE) who can design, architect, and develop AI-powered solutions for diverse business use cases. The ideal candidate should possess strong GenAI and AI/ML expertise, be capable of solutioning across multiple AI technology stacks, and have excellent business communication skills to engage with stakeholders and translate business requirements into scalable AI solutions.

Key Responsibilities

  • Design, architect, and implement AI/GenAI solutions for enterprise business use cases.
  • Engage with business stakeholders to understand challenges and recommend AI-driven solutions.
  • Build end-to-end AI applications using modern AI frameworks and cloud platforms.
  • Evaluate and adapt to different AI technologies, models, and platforms based on business needs.
  • Develop scalable RAG (Retrieval-Augmented Generation), AI Agents, and LLM-based applications.
  • Integrate AI solutions with enterprise systems and APIs.
  • Optimize AI model performance, cost, scalability, and security.
  • Collaborate with cross-functional teams including Product, Engineering, Data Science, and Business teams.
  • Stay updated with the latest advancements in AI, GenAI, LLMs, AI Agents, and cloud AI services.
  • Prepare solution architecture documents, technical proposals, and client presentations.

Required Skills

4+ years of experience in AI/ML or Generative AI solution development.

Strong experience with LLMs (OpenAI, Claude, Gemini, Llama, Mistral, etc.).

Hands-on experience building

RAG pipelines, AI Agents, Agentic AI, and prompt engineering.

Experience with AI frameworks such as:

LangChain

  • LangGraph
  • LlamaIndex
  • Semantic Kernel
  • CrewAI / AutoGen (preferred)
  • Strong programming skills in Python
  • Experience with vector databases such as Pinecone, ChromaDB, Milvus, Weaviate, or FAISS.
  • Experience with cloud AI platforms (Azure AI Foundry, Azure OpenAI, AWS Bedrock, Google Vertex AI, etc.).
  • Good understanding of MLOps, model deployment, monitoring, and AI governance.
  • Experience integrating AI solutions using REST APIs and microservices.
  • Familiarity with containerization (Docker, Kubernetes) is an advantage.