Software Engineer, Public Sector - New Grad

Scale AI•San Francisco, CA

3d•$124,000 - $162,000•Onsite

About The Position

Public Sector engineers build the core product including the systems required to ingest and process federal datasets that support real-time decision-making in contested environments. As a New Grad Software Engineer on this team, you will own meaningful, mission-facing work from day one: shipping features, sitting with the government stakeholders who use them, and iterating fast. Example Projects: Build multi-layered guardrails that keep agents safe and predictable in high-stakes federal environments Optimize data retrieval for agents, including RAG pipelines over large, heterogeneous federal datasets Build orchestration for fleets of asynchronous agents running long-horizon tasks Develop systems that automatically alert users to deviations and anomalies in incoming data Create interfaces that illustrate how an agent reached a decision, so operators can audit and trust its output Develop data pipelines and ML infrastructure that make previously siloed government data sources accessible to agents Build evaluation infrastructure that measures model reliability against mission requirements Ship full-stack tooling that lets analysts query, visualize, and explore mission data Deploy and harden applications into secure, air-gapped, and cloud-native government environments

Requirements

A graduation date in Fall 2026 or Spring 2027 with a Bachelor's degree (or equivalent) in a relevant field (Computer Science, EECS, Computer Engineering, Statistics)
Product engineering experience such as building web apps full-stack, integrating with relevant APIs and services, talking to users, figuring out 'what' to build and then iterating
Previous Product/Software Engineering internship experience
Track record of shipping high-quality products and features at scale
Experience building systems that process large volumes of data
Experience with Python, Typescript, React, and/or MongoDB
Strong written and verbal communication — you will work directly with government stakeholders and must be able to explain technical concepts to non-technical audiences
Comfort with ambiguity and evolving requirements, and a willingness to learn new domains quickly

Nice To Haves

Hands-on experience with LLMs, evaluations, or agentic systems — whether from internships, research, or personal projects
Familiarity with cloud platforms (AWS, Azure, GCP), containerization (Docker), and orchestration (Kubernetes)
Exposure to ETL, data modeling, data warehousing, or data governance
Prior experience with, or demonstrated interest in, national security, defense, or civil government technology
Open source contributions or a portfolio of shipped side projects

Responsibilities

Build multi-layered guardrails that keep agents safe and predictable in high-stakes federal environments
Optimize data retrieval for agents, including RAG pipelines over large, heterogeneous federal datasets
Build orchestration for fleets of asynchronous agents running long-horizon tasks
Develop systems that automatically alert users to deviations and anomalies in incoming data
Create interfaces that illustrate how an agent reached a decision, so operators can audit and trust its output
Develop data pipelines and ML infrastructure that make previously siloed government data sources accessible to agents
Build evaluation infrastructure that measures model reliability against mission requirements
Ship full-stack tooling that lets analysts query, visualize, and explore mission data
Deploy and harden applications into secure, air-gapped, and cloud-native government environments