Software Development Engineer - AI Enablement
About the role
Auger is building an autonomous operating system for the supply chain. Our customers rely on Auger to understand reality and change it: reporting, AI-powered decision support, and write-back execution systems that operate at scale. This role is data-centric software engineering.
Responsibilities
- Deliver end-to-end on assigned pipelines and transformation work
- Help troubleshoot production issues
- Consistently improve quality through tests, checks, and sound operational habits
- Build and maintain data pipelines lifecycle
- Ship production-grade transformation logic and operational outputs, using schema contracts and measurable validation
- Build and maintain the integration points between data pipelines and ML pipelines
- Implement schema-bound datasets that transform pipeline outputs into ML-ready inputs, and write ML results back to the semantic layer following established contracts
- Contribute to schema design and enforce data contracts that keep model logic cleanly separated from the system of record
- Operate what you build: monitoring and alerting as appropriate, participating in incidents remediations, and following through so issues do not repeat
- Practice test-driven habits for data: clarify correctness for the datasets you touch; add automated checks and regression coverage where it matters; turn bugs and incidents into fixes that stick
- Partner with product, science, and platform teammates to clarify requirements, flag tradeoffs early, and deliver work that holds up to customers
Requirements
- Degree in Computer Science, Mathematics, Statistics, or another data-intensive discipline (or equivalent practical experience)
- 4+ years of professional development experience with strong hands-on SQL and Python in production (Spark or equivalent large-scale batch processing preferred; Scala/Flink/Beam a plus)
- 3+ years in data work (structured and semi-structured), modern warehouses/lakehouses, and practical schema design in evolving domains
- Ownership mindset on production systems: you debug methodically, improve reliability over time, and connect your work to customer/product outcomes
- Hands-on experience with lakehouse/warehouse patterns, incremental processing, and basic performance/cost awareness
- Notebook fluency and the judgment to structure notebook work so it is reviewable and promotable
- Validation-first habits for data: meaningful checks between layers, DQ where it counts, and regression protection for critical transforms
- Agent-native fluency with verification—you treat generated SQL/pipelines as proposals until proven
- Clear communication and collaboration: you ask good questions, drive work to completion, and leave the codebase better than you found it
- A plus if you have experience in supply chain, planning, or fulfillment domains
Qualifications
- Experience with supply chain, planning, or fulfillment domains is a plus
Skills
- Data engineering
- SQL
- Python
- Spark or equivalent large-scale batch processing
- Scala/Flink/Beam
- Modern warehouses/lakehouses
- Schema design
- Incremental processing
- Performance/cost awareness
- Notebook fluency
- Agent-native fluency with verification
- Clear communication and collaboration
Benefits
Compensation & Benefits: As part of our commitment to People Powered Greatness, we invest in our team members with competitive compensation and a comprehensive benefits package to support your health, financial future, and daily life. The package includes medical, dental, and vision coverage, a 401(k) with company match, and commuter benefits. Total compensation may include a combination of a competitive base salary and equity. Your initial placement within our salary range will be based on your experience, qualifications. The base pay range for this role is $150,000 – $200,000 per year.
Pay
$150,000 – $200,000 per year
Schedule
N/A