About the role
We are looking for a Software Development Engineer II (SDE-II) with strong backend skills and hands-on experience in data engineering, time-series analysis, and API development. You will design and build scalable APIs, develop data connectors, and work on real-time process optimization and simulation software, contributing to production-grade, reliable engineering solutions.
You will collaborate with cross-functional teams to capture and process time-series events, build intelligent data pipelines, and develop robust microservices that power our core platform. The ideal candidate brings solid fundamentals in system design and concurrency, along with fluency in Python's data science tooling.
What you will do
API development
- Design, develop, and maintain RESTful APIs using FastAPI.
- Build and integrate Model Context Protocol (MCP) servers for agentic and AI-powered applications.
- Develop and maintain data connectors that interface with internal and external systems.
Data engineering
- Capture, process, and store time-series event data efficiently at scale.
- Design and implement data pipelines for ingestion, transformation, and analytics.
- Work with PostgreSQL and TimescaleDB on relational data modeling, query optimization, and schema design.
Simulation software
- Develop physics-based simulation software for domain-specific modeling requirements.
- Collaborate with domain experts to translate physical models into software.
- Ensure simulation accuracy, performance, and maintainability.
System design & concurrency
- Design scalable, maintainable system architectures for complex engineering problems.
- Implement multiprocessing and multithreading solutions for performance-critical workloads.
- Write clean, testable, well-documented code that follows engineering best practices.
What you bring
- 3–5 years of professional software development experience with a strong Python background.
- Proficiency in system design, multiprocessing, and multithreading.
- Strong SQL skills with hands-on PostgreSQL experience.
- Data engineering experience, including a solid understanding of time-series data capture, storage, and processing.
- Hands-on experience with Pandas, NumPy, and scikit-learn for data manipulation and modeling.
- Practical experience with time-series modeling techniques and libraries.
- Experience building and deploying RESTful APIs with FastAPI and asyncpg, including authentication and authorization.
- Understanding of the Model Context Protocol (MCP) and agentic integration patterns.
- Demonstrated experience building data connectors and integrations.
Nice to have
- Experience with DevOps practices, including CI/CD pipeline design and automation.
- Familiarity with AWS and/or Azure for deploying and managing services.
- Exposure to containerization (Docker) and orchestration (Kubernetes).
- Contributions to open-source Python, data engineering, or AI/ML projects.
- Experience with physics-based simulation or scientific computing.