Job Description
Description /n

About the Role
/n 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. /n

Key Responsibilities
/n /n
- Design, architect, and implement AI/GenAI solutions for enterprise business use cases. /n
- Engage with business stakeholders to understand challenges and recommend AI-driven solutions. /n
- Build end-to-end AI applications using modern AI frameworks and cloud platforms. /n
- Evaluate and adapt to different AI technologies, models, and platforms based on business needs. /n
- Develop scalable RAG (Retrieval-Augmented Generation), AI Agents, and LLM-based applications. /n
- Integrate AI solutions with enterprise systems and APIs. /n
- Optimize AI model performance, cost, scalability, and security. /n
- Collaborate with cross-functional teams including Product, Engineering, Data Science, and Business teams. /n




- Stay updated with the latest advancements in AI, GenAI, LLMs, AI Agents, and cloud AI services. /n
- Prepare solution architecture documents, technical proposals, and client presentations. /n /n Required Skills /n /n
- 4+ years of experience in AI/ML or Generative AI solution development. /n
- Robust experience with LLMs (OpenAI, Claude, Gemini, Llama, Mistral, etc.). /n
- Hands-on experience building RAG pipelines, AI Agents, Agentic AI, and prompt engineering. /n
- Experience with AI frameworks such as: /n
- LangChain /n
- LangGraph /n
- LlamaIndex /n
- Semantic Kernel /n
- CrewAI / AutoGen (preferred) /n
- Strong programming skills in Python. /n
- Experience with vector databases such as Pinecone, ChromaDB, Milvus, Weaviate, or FAISS. /n
- Experience with cloud AI platforms (Azure AI Foundry, Azure OpenAI, AWS Bedrock, Google Vertex AI, etc.). /n
- Good understanding of MLOps, model deployment, monitoring, and AI governance. /n
- Experience integrating AI solutions using REST APIs and microservices. /n
- Familiarity with containerization (Docker, Kubernetes) is an advantage. /n

📌 Forward Deployment Engineer (Sydney)
🏢 Capstone Recruitment
📍 Sydney