Software Engineer - Data Infrastructure

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.

We’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.

• 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

We know great candidates don’t always meet every requirement listed in a job description. If the role excites you and you believe you can make an impact at Assembled we encourage you to apply. We value diverse perspectives and are committed to building an inclusive workplace where everyone feels like they belong and has the opportunity to do their best work. We look forward to hearing from you!

For United States Applicants:
Assembled participates in E-Verify and will provide the federal government with your Form I-9 information to confirm that you are authorized to work in the United States.
For United Kingdom Applicants:
Assembled is required to verify your right to work in the UK and will conduct a Right to Work check prior to employment in accordance with applicable law.

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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