Software Engineer, Generative AI

Come grow with us at the frontier of AI. ArcFusion is expanding rapidly, and we are looking for passionate engineers to help us deliver the most exciting GenAI projects in the region. We are fully focused on staying ahead of the curve in Enterprise AI, building solutions that truly help our clients. If you are looking for a high-performing and supportive team where you can work on cutting-edge tech and accelerate your career, we'd love to meet you. The Role You'll design, develop, and maintain software systems with integrated generative AI: building APIs, designing databases, writing comprehensive tests, deploying to production, and supporting what you ship. GenAI is your specialization, not your whole job. You own the product end to end, interface included. You'll build the UI that enterprise users actually touch, often without a designer beside you. We want someone who notices when spacing is inconsistent, who has a view on what to cut, and who can take a half-formed brief and come back with something that works and looks considered. We also move fast with ideas. We use GenAI coding tools to prototype and validate concepts, and we're looking for engineers comfortable doing the same: turning an idea into a working proof of concept before investing in a full build. What You'll Do ● Design, implement, and maintain scalable, robust generative AI systems that meet performance, cost, and latency requirements ● Build and maintain the production backend services and APIs that power AI-driven applications ● Build the user-facing side of those applications, creating interfaces that are clear, consistent, and genuinely pleasant to use ● Make product calls: decide what's worth building, what to cut, and what the user actually needs ● Implement comprehensive testing strategies (unit, integration, and end-to-end), including evaluation frameworks and monitoring for AI systems ● Rapidly prototype and build proofs of concept using AI-assisted development tools to validate ideas, demonstrate feasibility, and iterate quickly ● Participate in code and design reviews, and contribute to engineering best practices for production AI systems ● Identify potential applications of generative AI for clients and advise on their implementation What We're Looking For ● 3+ years building production-ready software, with exposure to ML or data engineering ● Strong Python. Other modern languages are a plus ● Hands-on LLM experience, including prompt engineering, RAG architectures, and agentic workflows using frameworks like LangChain or LangGraph ● Real frontend ability and an eye for craft. React or similar, plus genuine care about spacing, alignment, typography, colour, and consistency. You can make an interface look considered without a designer holding your hand ● Product judgment. You can look at a vague requirement and work out what should actually get built, and say so ● Clear communication. You can explain both technical and design decisions to technical and non-technical audiences, and you take critique well on both Nice to Have ● Familiarity with vector databases (Pinecone, Weaviate, Qdrant, pgvector) or other NoSQL technologies ● Experience on a cloud platform such as Azure, AWS, or GCP ● Experience with design systems or component libraries (Tailwind, shadcn/ui), or fluency reading Figma Show Us Something Along with your application, send us something you've built that you're proud of the way it looks and feels. A live app, a side project, a repo with real UI work. One thing you can talk through in depth beats a long list. If it isn't public, screenshots plus a short note on the decisions you made are perfect. What We Value We believe the best solutions come from open collaboration. We're looking for engineers who don't just execute tasks, but actively contribute ideas, challenge assumptions, and speak up when they see a better approach, including when the better approach is "this isn't good enough yet." If you thrive in an environment where your voice matters and continuous improvement is the norm, you'll fit right in. And if you're missing some of the above, don't let that stop you. We care more about your fundamentals, how quickly you learn, and whether you care about the quality of what you ship than about ticking every box on a list.