AI Engineer
Location: Fully Remote (United States – PST Hours Preferred)
Employment Type: 6-Month Contract (View to Extend)
Our client is seeking an experienced AI Engineer to design, build, and deploy enterprise AI solutions that solve complex business challenges. This is a client-facing opportunity where you'll work alongside business stakeholders to develop scalable, production-ready AI platforms that deliver measurable business value.
Key Responsibilities
Location: Fully Remote (United States – PST Hours Preferred)
Employment Type: 6-Month Contract (View to Extend)
Our client is seeking an experienced AI Engineer to design, build, and deploy enterprise AI solutions that solve complex business challenges. This is a client-facing opportunity where you'll work alongside business stakeholders to develop scalable, production-ready AI platforms that deliver measurable business value.
Key Responsibilities
- Design, build, and deploy production-grade Agentic AI platforms and multi-agent systems.
- Develop and optimise RAG pipelines, integrate Large Language Models (LLMs), and deliver enterprise AI solutions.
- Engineer scalable cloud-based AI applications, APIs, and microservices following MLOps best practices.
- Collaborate directly with clients through discovery workshops, solution design sessions, and technical presentations.
- 3+ years of hands-on AI/ML engineering experience delivering production AI solutions.
- Experience building Agentic AI systems using frameworks such as LangChain, LangGraph, AutoGen, CrewAI, or similar.
- Strong experience with LLMs, prompt engineering, Retrieval-Augmented Generation (RAG), vector databases, Python, SQL, REST APIs, and microservices.
- Excellent communication skills with the ability to engage business stakeholders and translate complex AI concepts into practical solutions.
- Experience with Azure AI Studio, Azure OpenAI Service, Anthropic Claude, AWS, and Google Cloud Platform (GCP).
- Experience working with vector databases including Pinecone, Weaviate, or ChromaDB.
- Experience applying MLOps best practices for AI deployment, monitoring, and scalability.
- Previous experience delivering AI solutions within a client-facing consulting or professional services environment.
