Datacurve AI is building a gamified developer platform for engineers to create high-fidelity datasets that advance LLM frontiers. This Software Engineer role focuses on the technical lifecycle of data pipelines, from defining new data formats with partner labs to delivering tooling, environments, documentation, and QA to scale these formats. The role involves end-to-end project ownership, championing developer experience, ensuring quality and governance, and continuously improving reliability and contributor success rates.
Good To Have:
Co-author specs/RFCs with frontier lab researchers; design schemas, metadata, and versioning for new task/trajectory formats.
Ship tooling, sandboxes, CLIs/SDKs, and capture/instrumentation to make contribution flows fast and safe.
Experience designing or running evaluations for LLM outputs to measure and track quality, accuracy, or other performance metrics.
Familiarity with building tools for other developers, such as CLIs, SDKs, or internal dashboards.
Experience with cloud infrastructure (AWS), Docker, and CI/CD pipelines.
Must Have:
Own projects end-to-end, from initial prototyping to ongoing maintenance, bug fixing, and iteration.
Own developer experience pipelines end-to-end, from prototyping tooling to productionizing workflows.
Create clear, concise guidelines and documentation to empower data contributors and ensure high-quality inputs.
Develop and manage quality standards for projects, including training and aligning content reviewers.
Implement automated checks, eval harnesses, reviewer workflows, and data quality bars.
Monitor, debug, and continuously improve reliability, latency, and contributor success rates.
Excellent written communication skills to explain complex concepts to a less technical audience.
An organized and process-oriented mindset, meticulous about quality.
Foundational full-stack skills, with experience in React and at least one modern backend language (e.g., Python, Node.js, Go).
Strong technical judgment and a pragmatic mindset, balancing speed with quality.
Deep resourcefulness with AI, adept at prompt engineering and using AI tools.
Add these skills to join the top 1% applicants for this job
communication
performance-analysis
game-texts
react
prototyping
aws
node.js
ci-cd
docker
python
What You’ll Do
Own projects end-to-end, from initial prototyping to ongoing maintenance, bug fixing, and iteration based on feedback.
Own developer experience pipelines end‑to‑end: Prototype tooling for collecting new data formats → productionize workflow → iterate from developer experience
Champion DX: Create clear, concise guidelines and documentation to empower our data contributors and ensure high-quality inputs for your projects.
Quality & governance: Develop and manage the quality standards for your projects, which includes training and aligning content reviewers to ensure data consistency and accuracy. Implement automated checks, eval harnesses, reviewer workflows, and data quality bars; be hands on and in the weeds to align with reviewers on standards.
Maintain & iterate: Monitor, debug, and continuously improve reliability, latency, and contributor success rates.
What You’ll Do Sometimes
Define Frontier data formats: Co‑author specs/RFCs with frontier lab researchers; design schemas, metadata, and versioning for new task/trajectory formats.
Build developer tooling & environments: Ship tooling, sandboxes, CLIs/SDKs, and capture/instrumentation to make contribution flows fast and safe.
You’ll Succeed Here If You Have
Excellent written communication skills, with a proven ability to explain complex concepts to a less technical audience.
An organized and process-oriented mindset – you enjoy bringing structure to ambiguous problems and are meticulous about quality.
Foundational full-stack skills, with experience in React and at least one modern backend language (e.g., Python, Node.js, Go).
Strong technical judgment and a pragmatic mindset – you know how to balance speed with quality, recognizing the need for a scrappy solution versus when to invest in a robust architecture.
A deep resourcefulness with AI – you are highly adept at prompt engineering and using AI tools to find the fastest path to a solution.
Characteristics we’re looking for
Curiosity, pride in your work, desire to push the frontiers
Nice to Have
Experience designing or running evaluations for LLM outputs to measure and track quality, accuracy, or other performance metrics.
Familiarity with building tools for other developers, such as CLIs, SDKs, or internal dashboards.
Experience with cloud infrastructure (AWS), Docker, and CI/CD pipelines
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