Full Stack Engineer

Reports to: VP of R&D
Location: Remote (United States)

About The Company

Our client is a research-and-technology organization that uses data, experimentation, and applied engineering to help partner organizations operate more effectively. They have run 100+ randomized controlled trials (RCTs) on behavioral data and supported hundreds of partner organizations in increasing their impact. The environment is fast-paced and adaptive — the team is comfortable shifting quickly as priorities evolve, and is looking for candidates who thrive in that kind of setting.

About The Role

Our client is hiring a Staff Full-Stack Engineer to join their R&D team and help build the platforms that put data to work at the speed of thought. The R&D team is where the client places its most ambitious technical bets — moonshots (high-upside projects with uncertain payoffs) that need the muscle to break through.

Their flagship platform turns warehouse data into searchable, queryable large-scale databases, serves them through fast read-side APIs, and puts an LLM-powered agent in front of internal teams so they can analyze large operational datasets, build targeting segments, and design experiments. It's a Go backend (analytics, search, and geo services over DuckDB, SQLite, and AlloyDB), a React/TypeScript frontend with a type-driven visual grammar, an agent surface, and a CLI/SDK, all deployed on Google Cloud Platform and defined in Terraform. This person will work across all of it.

This is a role for an engineer who wants to own a product end-to-end: dbt model to API to UI to deploy, and back again. This role partners closely with the R&D lead, takes on projects that span the whole stack, and grows into owning systems that are already in use across the organization.

Responsibilities

• Build and ship features across the platform end-to-end, from the data model and Go API through the React UI and the Terraform that deploys them
• Extend the read-side platform (the analytics, search, and geo services) and the caching, batching, and connection-pooling that keep them fast under load
• Work on the LLM agent surface and the visual grammar that renders its output as interactive, legible blocks
• Maintain and extend the CLI and Go SDK alongside the UI
• Build and operate services and infrastructure on GCP, and participate in on-call and rapid response, including evenings and weekends during high-stakes operational windows
• Load-test and harden systems ahead of key operational deadlines, when the platform serves hundreds of partner organizations on a non-negotiable calendar
• Self-review and validate your own work before requesting review; review teammates' code, mentor less-experienced engineers, and document systems so others can use them without spelunking through code

How The Team Works

• Working systems, not code — code is a tool, not the job; the team builds systems that solve real problems for the people who use them
• Data is the foundation — most of the value created comes from how the data is organized underneath the system; the team invests in the dbt and read-side layers first
• Types are contracts — the team leans on a statically-typed backend and generates TypeScript from Go types so the two stay in sync, catching drift at compile time rather than in production
• Performance is a feature — fast read paths and fast feedback loops make everything downstream easier, including correctness
• Build it and run it — there's no separate ops team; infrastructure is code, and the team deploys what it writes and is on call for it, especially during high-stakes operational windows
• Small changes, shipped constantly — small, self-validated pull requests released to production several times a week, catching issues through monitoring rather than from a partner
• Reproducibility and simplicity — consequential operations are driven by immutable, declarative manifests, and the team does the simple thing first, adding complexity only when there's evidence it's needed

Requirements

• 7+ years building and operating production software end-to-end, across both backend and frontend
• Strong proficiency in a statically-typed backend language (the team uses Go) and in modern frontend development with TypeScript and React
• Experience with the data layer: SQL, a transformation framework like dbt, and a cloud data warehouse (BigQuery or similar)
• Experience deploying and operating services on a cloud platform (the team uses GCP: Cloud Run, GKE, Cloud SQL/AlloyDB) and managing infrastructure as code with Terraform
• A track record of leading technical work that spans multiple systems, and of scoping ambiguous problems end-to-end
• Strong written communication: able to document what you build and explain complex systems to non-engineers
• Comfortable operating in a fast-paced, mission-driven environment with shifting priorities

Nice To Have

• Experience building product surfaces on top of LLMs: agent workflows, tool calling, or structured generation
• Experience with high-performance read paths: columnar/analytical query engines (DuckDB), embedded databases (SQLite), connection pooling, and caching
• Experience in mission-driven, advocacy, or nonprofit sectors, including familiarity with the compliance and data-sensitivity considerations common to those environments
• Experience with large-scale behavioral, customer, or public-sector data
• Experience in on-call rotations and mentoring less-experienced engineers