Principal Software Engineer – AI Infrastructure
Summary
Principal Software Engineer leading greenfield AI infrastructure development—designing scalable backend platforms, ML inference pipelines, and cloud-native distributed systems using Java, Spring Boot, AWS, and Databricks.
- 10+ years of experience building and operating production-scale distributed systems.
- Proven experience designing and developing scalable backend platforms and services.
- Strong understanding of software architecture, system design, and cloud-native development.
- Experience translating ambiguous business requirements into technical solutions and execution plans.
Data & AI Platform Experience
- Experience building features for ML inference pipelines.
- Strong understanding of:
- Data processing frameworks
- Experience enabling machine learning workloads in production environments.
AI-Assisted Development
- Demonstrated proficiency with modern AI development tools, including:
- LLM-powered engineering workflows
- Agentic coding assistants
- Ability to effectively leverage AI tools to improve code quality, engineering productivity, and development speed.
Greenfield Product Development
- Proven track record of taking systems and platforms from 0 to 1.
- Comfortable working with undefined requirements and rapidly evolving priorities.
- Strong ownership mindset with the ability to drive initiatives independently.
- Ability to lead architectural discussions and influence technical direction.
- Experience communicating complex technical concepts across engineering and business stakeholders.
- Strong decision‑making skills around system design, scalability, reliability, and maintainability.
Technical Skills
- Java
- Spring Boot
- REST APIs
- AWS
- Compute, Storage, Networking
- IAM
- Cloud-native Architecture
AI / Data Platforms
- Databricks
Programming Languages
- Java
- Python
Development Tools
- AI-Assisted Development Tools
- Modern CI/CD Practices
Ideal Candidate Profile
You will be successful in this role if you:
- Have built AI-enabled platforms rather than simply consuming AI technologies.
- Have experience supporting ML inference and production AI systems.
- Use AI tools extensively to improve engineering efficiency and quality.
- Thrive in startup-like environments with high ownership and rapid execution.
- Enjoy solving complex technical challenges with limited direction.
- Collaborate effectively across Engineering, Product, and Data Science teams.
- Influence through technical excellence, architecture, and hands‑on execution.