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Great customer support requires human agents and AI in perfect balance, and Assembled is the only unified platform that orchestrates both at scale. Companies like Canva, Etsy, and Robinhood use Assembled to coordinate their entire support operation — in-house agents, BPOs, and AI — in a single operating system. With AI Agents that resolve cases end-to-end, AI Copilot for agent assistance, and AI-powered workforce management that optimizes both human and AI capacity, Assembled helps teams deliver faster, better service while making smarter decisions about how to staff and automate. Backed by $70M from NEA, Emergence Capital, and Stripe, we're building the platform that makes AI and human collaboration actually work. The Team: Our AI Products Team is building autonomous AI agents that handle the most challenging aspects of customer support and let human agents focus on high-value interactions. After launching the product's go-to-market motion, the Assist product line grew 5x in just 3 months to millions of ARR, with a strong pipeline of deals for even more growth. We're already deploying our systems at leading tech companies like Canva, Patreon, and Babylist, giving us complex real-world scenarios to solve with rapid feedback loops. The engineering challenges are significant: building autonomous agents that can reliably handle customer interactions, designing systems that scale across communication channels, and pushing the boundaries of what's possible with current LLM technology. Operating as an team led by CTO John Wang, we're focused on eliminating low-leverage support work and helping agents send faster, more accurate replies. Examples of what you might work on: Scaling LLMs with Golang; Enhancing RAG results with Reciprocal Rank Fusion and Hybrid Search; Pioneering new LLM evaluation techniques
Job Responsibility:
Build foundational new features: Develop product features from the ground up, such as implementing translation capabilities powered by LLMs and intelligent categorization of incoming tickets
Improve LLM model results: Enhance our retrieval augmented generation engine using techniques like vector search, document re-ranking, and hypothetical document embeddings
Develop LLM Infrastructure: Architect the abstractions that enable the integration of various types of LLMs tailored for different applications
Engage with customers: Collaborate with our customers (both support agents and managers) to understand their needs, how they interact with our product, and how we can improve their lives
Wear many hats: Be versatile in roles — coding, user research, planning, brainstorming, interviewing, and cross-team collaboration
Shape the team culture: Encourage a startup mentality that’s all about staying positive, aiming for top-notch product quality, and taking initiative
Requirements:
5+ years of experience in software engineering as an individual contributor
Highly ambitious and driven and set high goals for yourself and others
Put customers first, focusing on real problem-solving and making life easier for support agents
Enjoy fast-paced environments and can quickly adjust when new insights come from customers or prospects
Have a bit of a maverick streak that helps you come up with creative solutions for tough problems
Have made a noticeable impact on small teams and have solid experience contributing in startups or smaller companies
Have worked with LLMs and are excited to dive into them every day
Stay humble and open to feedback, value teamwork, and are always ready to learn and grow
What we offer:
Generous medical, dental, and vision benefits
Paid company holidays, sick time, and unlimited time off
Monthly credits to spend on each: professional development, general wellness, Assembled customers, and commuting
Paid parental leave
Hybrid work model with catered lunches everyday (M-F), snacks, and beverages in our SF & NY offices