Remote | Software Engineer, Data Platforms — $200,000–$280,000/year

24-Mag•New York, NY

2d•Remote

About The Position

We are sharing a specialised full-time opportunity for Software Engineers with strong expertise in Python, TypeScript, full-stack development, data platforms, and AI-assisted engineering workflows to build and maintain production systems supporting advanced human-data and AI operations. Selected professionals will own features end-to-end across backend services, data pipelines, databases, and React-based frontends. The role combines traditional full-stack engineering with research-oriented development, using coding agents as a core development workflow while collaborating closely with research engineering, operations, and product teams.

Requirements

Bachelor's degree in Computer Science, Computer Engineering, Software Engineering, or a related discipline, or equivalent practical experience
Approximately 0–5 years of professional software engineering experience, or strong shipped projects as a recent graduate
Strong fundamentals in Python and TypeScript
Experience building CRUD applications using frameworks such as FastAPI, Flask, React, or comparable technologies
Working knowledge of relational or document databases including PostgreSQL, MongoDB, SQLite, or similar systems
Experience deploying services to a major cloud platform such as GCP, AWS, or Azure
Practical experience using coding agents such as Claude Code, Cursor, Codex, or comparable tools as part of regular engineering work
Ability to turn desired outcomes into technical plans, direct coding agents, verify results, and identify architectural issues
Understanding of agent loops, MCP, tool and data integrations, permissions, and security
Familiarity with context management, RAG, and evaluations for testing agent workflows

Nice To Haves

Exposure to reinforcement-learning concepts or environments is advantageous
Experience with coding-data pipelines or task-authoring platforms is beneficial
Familiarity with CI/CD, deployment pipelines, and DevOps fundamentals is advantageous
Contributions to team projects, open-source software, or startup environments are beneficial

Responsibilities

Design and ship production-ready features across backend APIs, data pipelines, and React frontends
Build and maintain backend services using Python frameworks such as FastAPI or Flask
Develop TypeScript-based frontend and platform components
Own features from initial requirements and architecture through implementation, testing, and deployment
Build reliable systems that support day-to-day expert and operational workflows
Own client-facing data delivery workflows, including exports, access control, and platform reliability
Contribute to data modelling, schema design, and query-performance optimisation
Work across relational and document databases such as PostgreSQL, MongoDB, or SQLite
Build and maintain data pipelines supporting production platform requirements
Troubleshoot production issues and improve system resilience, observability, and reliability
Use coding agents as a primary development workflow for implementation and iteration
Scope engineering work around desired outcomes and direct multiple coding agents where appropriate
Review agent-generated changes at the architectural and systems level
Identify technical, security, or design issues that automated coding workflows may miss
Improve frameworks, checks, and evaluations that enable faster agent-driven development without sacrificing engineering quality
Partner with research engineering, operations, and product teams to translate platform requirements into production systems
Convert ambiguous product or research needs into scoped technical plans and implementation workflows
Work with agent loops, MCP, tool integrations, data integrations, permissions, and security considerations
Apply context management, RAG, and evaluation techniques when testing agent-based workflows
Communicate architecture decisions, trade-offs, implementation risks, and technical constraints clearly