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.