Software Engineer, Data Infrastructure (AI)

TL;DR

Software Engineer, Data Infrastructure (AI): Architecting and building foundational data infrastructure and processing pipelines for simulation data with an accent on high-throughput, low-latency data ensembles for LLM consumption. Focus on designing novel data models, optimizing massive batch jobs, and ensuring seamless integration with government customer workflows.

Location: Must be based in the US (Federal Engineering role supporting US government agencies)

Company

Scale AI develops reliable AI systems for the world's most important decisions, providing high-quality data and full-stack technologies that power leading models for enterprises and governments.

What you will do

• Architect a unified data ensemble to aggregate simulation data, historical states, and user inputs for optimized LLM consumption.
• Build scalable, resilient data architectures from scratch to process massive quantities of simulation output via batch jobs.
• Design sophisticated relational data models representing massive, state-based simulation environments.
• Develop custom, ground-up systems to handle structural complexity and scale where open-source tools are insufficient.
• Lead technical standards for the data infrastructure team, driving rigorous code quality and architectural clarity.

Requirements

• 5+ years of backend or data infrastructure experience at a Senior, Staff, or Principal level.
• Expert-level proficiency in Rust, Go, C++, or highly optimized Python/Java, and Spark.
• Deep understanding of memory management, compute limits, and distributed systems architecture.
• Proven track record of optimizing high-throughput, low-latency data processing and parallel processing.
• Must be eligible and willing to obtain a US security clearance (Secret or TS/SCI).

Nice to have

• Active Secret or TS/SCI security clearance.
• Experience with LLM context optimization, vector embeddings, or agentic AI frameworks (e.g., advanced RAG).
• Domain experience with wargaming data, complex systems modeling, or distributed simulation protocols.
• Previous experience in a high-growth, 0-to-1 startup environment.

Culture & Benefits

• Comprehensive health, dental, and vision coverage.
• Retirement benefits and generous PTO.
• Learning and development stipend.
• Equity compensation grants.
• Commuter stipend eligibility.