Software Engineer, Data Platforms

Pay: $120,000–$160,000/year
Where: Remote
Type: Full-time
Eligibility: Country eligibility not stated. Check with the provider before applying.
Listing: Last verified Oct 6, 2026

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Overview

An AI-native full-stack engineering role building the company’s human-data platforms, owning features end to end: backend services, data pipelines and the frontends experts use every day.

The role sits between traditional full-stack and research engineering. Coding agents are the primary development workflow, working closely with research engineers, operations and product.

Responsibilities

Design and ship full-stack features across backend APIs, data pipelines and React frontends.
Own client-facing data delivery and platform infrastructure, including exports, access control and reliability.
Scope work around outcomes, direct coding agents (often in parallel), review changes at the architecture level, and iterate until shipped.
Build and maintain services in Python (FastAPI) and TypeScript.
Contribute to data modelling, schema design and query performance across relational and document databases.
Turn platform needs into production systems with research engineering, operations and product.
Improve the frameworks, checks and evals that make agent-driven development faster without losing quality.
Troubleshoot production issues and build resilient, observable systems.

Requirements

A degree in computer science, computer engineering, software engineering or a related field, or equivalent practical experience.
0–5 years of software engineering experience, or strong shipped projects as a recent graduate.
Strong Python and TypeScript, building CRUD applications with frameworks such as FastAPI/Flask and React.
Working knowledge of databases such as PostgreSQL, MongoDB or SQLite, and data-modelling principles.
Experience deploying services on GCP, AWS or Azure.
Coding agents such as Claude Code, Cursor or Codex as your default workflow, and able to explain how you use them.
Able to turn outcomes into plans, direct agents, verify results and spot architectural issues agents miss.
Understanding of agent loops, MCP, tool and data integrations, permissions and security.
Familiarity with context management, RAG and evals for agent workflows.

Preferred

Exposure to reinforcement-learning concepts or environments (tasks, actions, rewards).
Coding data pipelines or task-authoring platforms.
CI/CD, deployment pipelines and DevOps fundamentals.
Team projects, open-source software or startups.

Engagement and pay

Pay stated in the job description: base salary of $120,000–$160,000 per year, the national pay range for this full-time position.
Pay shown at the top of the job post: $200K–$280K per year.
The two figures differ; each is shown exactly as the source states it.
All employees are eligible for equity, and may receive performance-based bonuses depending on the role and company policy.
Benefits: up to 100% reimbursement of health-insurance premiums, paid time off, a 401(k) with a company match, and other benefits.
Full-time, remote. Start date: not stated.
The listing states 1 opening.

Eligibility

Location: remote. Country or residence limits: not stated in the listing.
Equal opportunity employer; reasonable accommodations are available during the application process.
The hiring process uses AI tools to help with screening and assessment, alongside human decisions.