全职 AI-Native Software Architect (Go or Python)(A252801) 工作, 薪水, AI Rudder Federal Territory 公司招聘中 - Ricebowl

About the Role

We are looking for an architect who can be trusted with an entire problem space—not only someone who produces architecture diagrams or recommendations. You will take ambiguous business goals and turn them into sound decisions, working prototypes, production systems, measurable outcomes, and continuous improvements.

You will own a clearly defined product or technical domain while remaining able to move quickly into adjacent projects as business priorities change. Our primary context includes commercial Voice AI and intelligent contact centre systems, where real-time interaction, low latency, reliability, multi-vendor integration, multi-cloud deployment, and on-premise delivery all matter.

This is an AI-native role. We expect you to treat AI and multiple agents as part of your everyday delivery system: deciding what to delegate, defining clear inputs and outputs, coordinating hand-offs, validating results, and retaining accountability for the final outcome.

What You Will Own

• Own a complete business or technical domain from problem definition and architecture through prototype, implementation, launch, measurement, and retrospective.
• Break down complex, ambiguous problems into cohesive, loosely coupled, independently testable workstreams that can be executed in parallel by people and AI agents.
• Design and evolve highly available, scalable, maintainable systems with clear service boundaries, API and event contracts, data flows, state machines, and failure-handling strategies.
• Make explicit trade-offs across latency, performance, availability, security, cost, delivery speed, and long-term evolution.
• Design for retries, timeouts, idempotency, cancellation, compensation, version compatibility, observability, auditability, graceful degradation, and human intervention.
• Use AI across research, architecture, coding, testing, debugging, documentation, and operational analysis while verifying critical outputs rather than accepting them blindly.
• Coordinate collaboration across product, engineering, quality, operations, security, and business teams; surface assumptions, risks, unknowns, and dependencies early.
• Move effectively across related projects, rapidly understand unfamiliar business flows and codebases, and identify the few decisions that matter most.
• Turn personal practices into reusable tools, skills, templates, engineering standards, and playbooks that help the wider team move faster.

What AI-Native Means Here

AI-native does not mean forwarding unverified model output to the team. It means building a disciplined delivery system around AI. You should be able to choose the right human and AI roles, define task contracts and acceptance criteria, run multiple agents when parallelism creates real value, review their work, resolve conflicting conclusions, and keep the final result reproducible and auditable.

The strongest candidates can use AI to accelerate the full loop from research and design to prototype, implementation, testing, and validation—and can make those working methods reusable by others.

What We Are Looking For

• Strong expertise in at least one language: You must be highly proficient in either Go or Python and able to design, implement, review, and troubleshoot production systems at code level. Expertise in both is welcome but not required.
• Architecture that reaches production: You have delivered complex systems involving distributed services, high concurrency, high availability, observability, disaster recovery, security, and controlled evolution.
• Depth and breadth: You have deep knowledge in at least one or two relevant areas—such as real-time media, speech systems, LLM inference, distributed systems, scheduling, cloud platforms, or reliability engineering—and enough breadth to make end-to-end decisions.
• Judgement under uncertainty: You can make high-quality decisions when information is incomplete, goals conflict, or resources are limited, and you can explain the trade-offs and likely second-order effects.
• Problem decomposition: You can turn a large, unclear goal into well-bounded modules, interfaces, milestones, and verification steps.
• Ownership and initiative: You do not wait for step-by-step instructions. You clarify assumptions, close information gaps, identify risks, coordinate resources, and keep the work moving until the outcome is achieved.
• Technical taste: You prefer simple, clear, maintainable designs and know how to avoid both short-term patchwork and premature platform building.
• Communication: You can lead architecture reviews, make complex topics understandable to different audiences, and create documents that allow others to continue the work independently.
• Mandarin: Fluent spoken Mandarin is required because this role regularly leads requirement discussions, architecture reviews, and delivery coordination with Mandarin-speaking product, engineering, and business stakeholders.
• English: Professional working proficiency is required for Malaysia-based collaboration, regional communication, and technical documentation.

Preferred Qualifications

• Experience with Voice AI, intelligent contact centres, real-time audio, ASR, TTS, LLMs, SIP, RTP, WebRTC, or FreeSWITCH.
• Experience with large-scale scheduling, streaming systems, dynamic multi-vendor routing, multi-cloud or multi-region architecture, and on-premise deployment.
• Experience balancing latency, reliability, cost, and conversational quality in a production system.
• A track record of taking systems from proof of concept and MVP through production scale.
• Experience leading complex delivery across multiple teams without relying solely on formal authority.
• Evidence that your tools, methods, or technical decisions have made other engineers and teams more effective.

What Success Looks Like

When an open-ended business or technical problem is assigned to you, you can quickly understand the goal and context, expose the critical assumptions and risks, compare viable approaches, make a clear recommendation, organise the right people and AI agents, and deliver a working, verifiable, maintainable result.

You are not only an adviser and not only a hands-on engineer. You are the person who can take ownership of an important domain, bring others with you, and reliably bring the result back.