Agentic Infrastructure Engineer for Scalable AI Research

Stanford University; Palo Alto (CA); On-site; USD 118,000 - 165,000; Full time

Job summary

Stanford Law School's Legal Innovation through Frontier Technology Lab (liftlab) seeks a Research Engineer to design and implement software systems that support its agentic AI research. You will build modular infrastructure to coordinate research agents, provision reproducible environments, run large-scale experiments, and ensure traceable results. Reporting to Directors Prof.

Julian Nyarko and Dr. Megan Ma, you will lead development, review code, and collaborate with researchers to advance

Qualifications

• Strong programming skills in Python and the ability to select, adapt, and quickly learn appropriate scientific programming tools and libraries.
• Demonstrated ability to design, develop, test, deploy, and maintain complex software systems.
• Strong understanding of modular software architecture, API integrations, data architecture, and data modeling.
• Ability to rapidly configure reproducible research environments and resolve complex software dependency and installation issues.
• Experience with scalable data processing, parallel or distributed execution, and performance optimization.
• Working knowledge of research design, statistics, and machine learning sufficient to implement and test computational methods in collaboration with researchers.
• Strong code review, debugging, quality control, and documentation skills, with attention to computational accuracy and reproducibility.
• Ability to translate evolving research specifications into reusable technical capabilities and communicate feasibility constraints and design tradeoffs clearly.
• Ability to plan engineering work, deliver against agreed milestones, and collaborate effectively with researchers and technical colleagues.

Responsibilities

• Translate research designed with the Directors into technical specifications, implementation plans, and milestones.
• Design and implement modular systems for deploying and coordinating research agents, integrating models and tools.
• Rapidly provision reproducible computing environments and build parallel or distributed experiment pipelines.
• Implement classifiers, baseline models, analytical tools, and evaluation harnesses for research needs.
• Lead code review, automated testing, debugging, and documentation for reproducible research.
• Maintain, troubleshoot, and optimize research applications and infrastructure while preserving reproducibility.
• Lead engineering delivery and mentor staff; set implementation guides and deployment standards.

Skills

Python

Software design

API integrations

Data modeling

Data processing

ML methods

Documentation

Education

Master’s degree in computer science, software engineering, data science, computational methods, or a related field

PhD in computer science, software engineering, data science, computational methods, or a related field, would be ideal

Tools

Docker

Kubernetes

Job description

Stanford Law School's Legal Innovation through Frontier Technology Lab (liftlab) seeks a Research Engineer to design and implement software systems that support its agentic AI research. You will build modular infrastructure to coordinate research agents, provision reproducible environments, run large-scale experiments, and ensure traceable results. Reporting to Directors Prof.

Julian Nyarko and Dr. Megan Ma, you will lead development, review code, and collaborate with researchers to advance