Job Description

Description 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.

Key Responsibilities n

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- Design, architect, and implement AI/GenAI solutions for enterprise business use cases.
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- Engage with business stakeholders to understand challenges and recommend AI-driven solutions.
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- Build end-to-end AI applications using modern AI frameworks and cloud platforms.
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- Evaluate and adapt to different AI technologies, models, and platforms based on business needs.
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- Develop scalable RAG (Retrieval-Augmented Generation), AI Agents, and LLM-based applications.
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- Integrate AI solutions with enterprise systems and APIs.
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- Optimize AI model performance, cost, scalability, and security.
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- Collaborate with cross-functional teams including Product, Engineering, Data Science, and Business teams.
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- Stay updated with the latest advancements in AI, GenAI, LLMs, AI Agents, and cloud AI services.
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- Prepare solution architecture documents, technical proposals, and client presentations.
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Required Skills nn
- 4+ years of experience in AI/ML or Generative AI solution development.
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- Solid experience with LLMs (OpenAI, Claude, Gemini, Llama, Mistral, etc.).
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- Hands-on experience building RAG pipelines , AI Agents, Agentic AI, and prompt engineering.
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- Experience with AI frameworks such as: n n
- LangChain
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- LangGraph
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- LlamaIndex
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- Semantic Kernel
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- CrewAI / AutoGen (preferred)
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- Strong programming skills in Python .
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- Experience with vector databases such as Pinecone, ChromaDB, Milvus, Weaviate, or FAISS.
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- Experience with cloud AI platforms (Azure AI Foundry, Azure OpenAI, AWS Bedrock, Google Vertex AI, etc.).
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- Good understanding of MLOps, model deployment, monitoring, and AI governance.
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- Experience integrating AI solutions using REST APIs and microservices.
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- Familiarity with containerization (Docker, Kubernetes) is an advantage.
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📌 Forward Deployment Engineer (Mid-Level Engineer) (Sydney)
🏢 Capstone
📍 Sydney