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 RoleWe’re looking for an experienced software engineer to help shape the foundation of Assembled’s data systems. You’ll join our Data Infrastructure team, a close partner to both our Core Infrastructure and AI Infrastructure teams, to own how data is modeled, stored, and served across the company. This work powers everything from customer-facing dashboards to internal analytics and AI-driven product features.
We're currently rebuilding our metrics infrastructure from the ground up. Our legacy Go-based system made it difficult to scale, maintain, and trust the metrics we expose. We’re building a new analytics stack that enables fast, reliable metric queries and simplifies the development of new reports. You’ll be joining at a pivotal moment—early prototypes are in place, and we’re working toward a full-scale production rollout and long-term migration.
The team also plays a central role in the development of Assembled’s AI platform, Assist. As we unify our WFM and AI products into a single Human + AI experience, the Data Infrastructure team is responsible for the analytics that help customers understand how Assist is adopted, how it impacts performance, and where to optimize. You’ll collaborate closely with the Assist team to build robust data models and systems that support this functionality.
One of the more unique challenges in this role is that our data infrastructure doesn't just support internal analytics—it powers customer-facing product experiences. While some outputs are traditional dashboards, others require near real-time responsiveness. As a result, our stack must support both large-scale analytical queries and low-latency, user-triggered interactions—capabilities that most analytics systems are not architected to handle simultaneously. We're building a unified system that can do both, without introducing mismatched data or duplicated definitions.
In this role you'll:Design and build systems that power both the storage and retrieval of analytical data
Own the transformation layer that models data for fast, consistent metric queries
Define and maintain the metrics layer that supports dashboards, exports, APIs, and internal tools
Collaborate with product, infrastructure, and Assist teams to build rich reporting experiences—like helping customers measure ROI on AI adoption
Manage scalable pipelines that move and transform production data for analysis
Instrument observability into the data platform, including freshness, lineage, and correctness
Have experience working with modern data warehouses (e.g., Snowflake, BigQuery) and understand their performance characteristics
Have built or maintained end-to-end ELT pipelines and are comfortable choosing the right level of precomputation
Have designed or worked closely with a metrics or semantic layer, and understand how to define metrics that are consistent, queryable, and performant across reporting surfaces
Are comfortable reasoning about systems tradeoffs—latency, cost, developer velocity, and reliability
Take pride in building systems that are clear, maintainable, and empower others
Have strong SQL fluency and are comfortable reading query plans, debugging slow queries, and optimizing for performance
Experience with semantic layer tools like Cube, MetricFlow, or Looker’s LookML
Familiarity with analytics-focused software engineering (e.g., event tracking, funnel analysis, experiment platforms)
Experience modernizing legacy data systems or planning large-scale migrations
Experience collaborating cross-functionally with AI/ML teams or product managers focused on AI systems
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
401(k) plan enrollment
Top Skills
What the Team is Saying
What We Do
Industry leaders like Etsy, Robinhood, and Stripe trust Assembled to provide customer-facing AI agents and workforce planning at scale. We automatically resolve millions of interactions through chat, email, and phone while optimizing staffing for hundreds of thousands of support professionals. Our mission is to elevate customer support through AI-powered software that makes life easier for customers and employees.
Why Work With Us
Assembled is built on the belief that great teams, like great support agents, lead with empathy, ownership, and action. We work transparently, give and receive feedback as a gift, and show up for each other across roles. It's a culture where titles take a back seat to impact, and everyone’s invested in building something that truly supports people.
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Hybrid Workspace
Employees engage in a combination of remote and on-site work.
For the majority of our roles we're hybrid, Monday & Thursday in-office
