AI Solutions Engineer (013-0996)
Hunt St
| Company | Hunt St |
| Category | Engineering |
| Location | Philippines |
| Remote | Remote |
| Employment | Full-time |
| Level | Not stated |
| Salary | Not stated by the employer |
| Posted | 19 Jun 2026 |
| Last verified | 10 Aug 2026 |
| Source | Employer ATS (workable) |
Description
Looking for Philippines-based candidates Job Role: AI Solutions Engineer Compensation range: $3,000 AUD - $4,000 AUD / Monthly Engagement type: Independent Contractor Agreement Work Schedule: This role is expected to align with the AU business hours (approx. 9 AM - 5 PM, Monday to Friday) for collaboration, but as a contractor, you’ll have flexibility in how you manage your time. Who We Are: At Hunt St, we help Australian companies hire top remote talent in the Philippines. For this role, you will be engaged directly by the client as an independent contractor. We are not an outsourcing agency. All of our roles are 100% remote so you'll be able to work from home. Who The Client Is: Our client is a well-established Australian telecommunications solutions provider with over two decades of industry experience. They specialize in delivering reliable voice, internet, cloud, and unified communication services to businesses of all sizes. Known for their customer-first approach and locally based support team, they help organizations stay connected through tailored, innovative, and scalable communication solutions. Role Overview: We are seeking an innovative AI Solutions Engineer to design, develop, and deploy intelligent AI-powered applications that enhance business operations and user experiences. In this role, you will build scalable AI solutions by integrating large language models (LLMs), developing robust APIs, and creating intuitive user interfaces. You'll collaborate with cross-functional teams to seamlessly embed AI capabilities into existing business systems, leveraging modern orchestration frameworks, Retrieval-Augmented Generation (RAG), and vector databases to deliver reliable, context-aware solutions. The ideal candidate is a hands-on engineer who thrives in a fast-paced environment, rapidly prototypes ideas, iterates based on feedback, and builds production-ready AI applications on AWS using modern Python frameworks. Key Responsibilities: Review and analyse internal business processes, customer interactions, and operational workflows to identify opportunities for AI-driven automation, efficiency improvements, and enhanced customer experiences. Design and develop AI solutions that address operational challenges, with consideration for how they can be standardized, packaged, and deployed across multiple customers and industries. Work closely with stakeholders to gather requirements, understand business needs, and translate them into scalable AI applications and workflows. Evaluate the performance of deployed AI solutions using productivity, service, and customer experience metrics, continuously refining outcomes. Identify repeatable business challenges and develop reusable AI frameworks, tools, and integrations that contribute to the company's AI solutions portfolio. Contribute to the development of commercial AI products by transforming successful internal solutions into customer-ready offerings. Build and maintain secure, high-performance APIs to support AI integrations and business applications. Develop intuitive, responsive front-end interfaces that enhance the user experience of AI-powered applications. Integrate large language models (LLMs) such as OpenAI, Anthropic, and other AI platforms into production-ready solutions. Implement Model Context Protocol (MCP) or similar integration patterns to enable seamless AI workflows and tool connectivity. Design and implement Retrieval-Augmented Generation (RAG) solutions using enterprise knowledge sources. Build, manage, and optimize AI knowledge bases and vector databases such as Pinecone, Weaviate, or similar platforms. Integrate AI capabilities into existing business systems, including CRM platforms and internal applications. Develop AI workflows and agent-based solutions using orchestration frameworks such as LangChain, Semantic Kernel, or equivalent technologies. Deploy, monitor, and optimize AI applications using AWS