Full Stack Engineer

 Posted 4 hours ago
     
โญ 5-10 years experience
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AI Summary

Build and ship AI-driven sales enablement products, focusing on LLM orchestration and RAG pipelines. Design scalable multi-tenant architectures and implement real-time voice and agentic workflows.

Hey, glad you're here ๐Ÿ‘‹

We know job hunting can feel a little overwhelming, endless tabs, endless job descriptions, and trying to figure out whether a company is actually the right fit (not just whether you fit the role).

So weโ€™ll keep this simple. Here's a look at the role, the team, and the impact you'll have at Hupo. If what you read gets you excited, we'd love to meet you!

About Hupo

We are an AI-native start-up building sales enablement products in the banking, financial services, and insurance industry; already trusted by dozens of enterprise customers (including Fortune 500 companies).

Role at a Glance

๐Ÿ‘” Title: Senior Full Stack Engineer - AI Products
๐Ÿค Team: Engineering
๐Ÿ“” Employment Type: Full-time
Location:
๐Ÿ“ Singapore: Hybrid
๐Ÿ“ Southeast Asia (SEA): Remote (Must align with SEA timezones)

What You'll Do

  • Build and ship AI-driven products across the sales lifecycle (lead qualification, meeting prep, live assistance, roleplay, outbound, follow-ups)

  • Develop LLM orchestration and RAG pipelines using CRM data, product knowledge, and customer context

  • Work on real-time and voice features, including low-latency pipelines, transcription, and in-call AI support

  • Design and implement agentic workflows (multi-step AI tasks, automation, outbound sequences)

  • Integrate with CRM systems, communication platforms, and enterprise data sources

  • Contribute to scalable, multi-tenant architecture for enterprise clients

  • Take features from concept to production, including design, implementation, and iteration

What We're Looking For

Must-Haves

  • 4+ years of experience in backend or full-stack engineering

  • Strong proficiency in Node.js and TypeScript

  • Experience building and shipping AI-powered features in production

  • Solid understanding of system design (APIs, async workflows, real-time systems, data modeling)

  • Comfortable working in fast-moving, ambiguous environments

Nice-to-Haves

  • Experience with LLM workflows, RAG pipelines, or agentic systems

  • Exposure to voice or real-time systems (STT, TTS, streaming)

  • Experience building multi-tenant SaaS platforms

  • Familiarity with cloud infrastructure (e.g. AWS)

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