Software Engineer, Data Systems & Infrastructure
Listed on 2026-10-25
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Software Development
Database Engineering, Backend Developer, Software Engineer
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Software Engineer, Data Systems & Infrastructure001 Lakewood, CO, US
Salary Range: $ To $ Annually
About the Role
This is a software role focused on data systems 'll help build the infrastructure software that stores and organizes synthetic data from our physics solvers, make five decades of engineering reports searchable and useful, and help build an internal knowledge AI that captures engineering know-how and connects it to our software.
Most of your time will go to software development. You'll also play a real part in a major infrastructure project: moving our storage and core IT services into our new data center space. You'll work alongside our infrastructure team and learn as you go, which is a great chance to see how data systems work from the hardware up to the application.
What You'll Do
Data systems and software (about 70–80%)
- Help build and maintain the data infrastructure software behind our synthetic solver data for Physics AI.
- Help build the data foundation for an internal knowledge AI tool. This means capturing and structuring engineering insights, indexing them for retrieval, and managing access controls so the tool only reaches the data and EMA software it's permitted to.
- Digitize, index, and improve search across about 50 years of technical reports and engineering files.
Infrastructure
- Help plan and carry out the migration of file storage to Dell Power Scale OneFS. This includes data moves, share and permission mapping, and checking that everything arrived intact.
- Support moving IT services into our new data center space.
- Serve as backup to the infrastructure team for issues with the systems behind the data warehouse.
- Document systems and procedures as you go.
What We're Looking For
- A BS in Computer Science, Computer Engineering, or a related field, or equivalent experience.
- SQL, graph databases, and basic data modeling.
- Exposure to LLM tooling: retrieval-augmented generation (RAG), embeddings, vector search, or MCP.
- Git and general software engineering practices: testing, code review, writing things down.
- Working comfort with Linux and Windows environments and basic networking concepts (DNS, subnets, VPNs).
- Curiosity, and the ability to pick up unfamiliar systems on your own.
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