Position: Wand AI - Back-End Team Lead
Company: SD Solutions
Category: Python
Experience required: 5y
English level: upper

## What hard skills do we need?

- B.Sc. in computer science or a related field.
- **3+ years** of experience managing BE teams working on SaaS systems.
- **7+ years** of experience building distributed large-scale SaaS systems.
- **3+ years** of design and implementation of SaaS Kubernetes applications built out of microservices.
- Expert in Python and development methodologies with application to SaaS BE (clean code, frameworks, API design, etc.)
- Experience with different types of data storage (SQL, NoSQL, search engines, big data tools, object stores). **PostgreSQL** and **MongoDB** – **must.**
- Experience with modern CI/CD and GitOps methodologies.
- Fluent English

**Advantages:**

- M.Sc. in computer science or a related field.
- Experience with user-defined workflows (e.g., Airflow).

## What will you do with us?

- Own, design, and develop Wand AI backend: be responsible for Kubernetes application design and implementation of major features and services.
- Be responsible for the end-to-end feature/service lifecycle: starting from design and architecture, through implementing, testing, and releasing the feature.
- Design and evolve software managing in-environment service discovery and configuration of microservices.
- Mentor, perform code reviews, evaluate implementations and provide feedback about potential tool improvements.
- Collaborate with Product Managers, Product Designers and other Software Engineers.

About the company:
Wand delivers the simplest approach to designing, building, and managing AI-based business solutions, streamlining its full lifecycle from data cleansing and quality improvement to AI modelling, AI stress testing, deployment and MLOps, thus reducing the needed time and workforce. 

Each Wand-built solution is automatically managed, monitored, and governed to deliver high-performance into production and at scale. Users of Wand can track the organizational AI status from the single solution level to department and firm-wide levels – taking smarter data-driven decisions.