Forward Deployment Engineer (Mid-Level Engineer)

Capstone; Sydney; On-site; AUD 120,000 - 180,000; Full time

Job summary

Capstone in Sydney, Australia seeks an experienced AI Engineer (FDE) to design and develop AI-powered solutions across diverse business use cases. You will engage with stakeholders to translate requirements into scalable AI applications, including end-to-end AI systems and GenAI-driven architectures.

The ideal candidate brings strong GenAI/AI/ML experience, hands-on work with LLMs, RAG pipelines, AI Agents, and proficiency in Python, plus familiarity with cloud AI platforms and MLOps for

Qualifications

• 4+ years in AI/ML or GenAI solution development.
• Strong experience with LLMs (OpenAI, Claude, Gemini, Llama, Mistral).
• Hands-on with RAG pipelines, AI Agents, and prompt engineering.
• Experience with AI frameworks: LangChain, LangGraph, LlamaIndex, Semantic Kernel.
• Strong Python programming skills.
• Vector databases experience: Pinecone, ChromaDB, Milvus, Weaviate, FAISS.
• Cloud AI platforms: Azure AI Foundry, Azure OpenAI, AWS Bedrock, Vertex AI.
• Good understanding of MLOps, deployment, monitoring, governance.
• Experience integrating AI solutions via REST APIs and microservices.
• Familiarity with Docker and Kubernetes is an advantage.

Responsibilities

• Design, architect, and implement AI/GenAI solutions for enterprise 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.

Skills

LLMs

RAG pipelines

AI Agents

Python

Vector databases

Cloud AI platforms

MLOps

REST APIs

Containerization

Tools

LangChain

LangGraph

LlamaIndex

Semantic Kernel

CrewAI / AutoGen

Job description

Description 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.