Full-stack Engineer (Python, Node.js, Typescript) for AI Training project

Gramian Consultancy is a boutique consultancy specializing in IT professional services and engineering talent solutions. With a strong background in software engineering and leadership, we help companies build high-performing teams by matching them with professionals who truly fit their needs.

Role Overview

We are looking for a highly skilled Full-Stack Engineer with a focus on Python, Node.js, and TypeScript to contribute to our AI training project. This role will be pivotal in building and optimizing a sophisticated data ecosystem designed for AI model training and evaluation. You will engage in a variety of tasks, including designing APIs, developing web applications, and optimizing data processing workflows in a collaborative and innovation-driven environment.

NOTE: In this project you will not build a project, but specifically generate data to improve model performance for one of the biggest foundational model companies.

Duration: 3 months

Commitment: 40h/week, 4h/day overlap with PST

Model: Contract, time and material

Location: 100% Remote (LATAM, Europe, MENA)

Key Responsibilities

• Write, review, and debug code across multiple languages
• Design tasks and evaluation scenarios for coding, reasoning, and debugging
• Investigate LLM outputs and identify hallucinations, regressions, and failure modes
• Build reproducible dev environments using Docker + automation tools
• Develop scripts, pipelines, and tools for data generation, scoring, and validation
• Produce structured annotations, judgments, and high-quality datasets
• Run systematic evaluations that help improve model reliability and reasoning

Requirements

• Experience using LLM coding tools (Cursor, Copilot, CodeWhisperer)
• Strong hands-on coding experience (professional or research-based) in one or more of:

• Python, JavaScript / Node.js, TypeScript
• (Additional languages like Go, Java, C++, C#, Rust, SQL, R, Dart, etc. are a plus)

Solid experience with Linux + Bash, scripting, and automationStrong with Docker, reproducible environments, and dev containersAdvanced Git skills (branching, diffs, patches, conflict resolution)Solid understanding of testing and QA (unit, integration, negative, edge-case focused)Ability to reliably overlap with 8am–12pm PST

Nice-to-Haves:

• Experience with dataset creation, annotation, evaluation, or ML pipelines
• Familiarity with benchmarks like SWE Bench or Terminal Bench
• Background in QA automation, DevOps, ML systems, or data engineering

Benefits

• Work in a fully remote environment.
• Opportunity to work on cutting-edge AI projects with leading LLM companies.