Senior Python Backend Developer: Team Lead
About Seed-X:
Seed-X is an innovative, high-growth AgTech company revolutionizing the AgriTech industry, backed by Nacre Capital ( a venture builder). We leverage proprietary AI, machine vision, and deep learning algorithms to analyze seeds at the individual level, providing unmatched insights into genetic purity, quality, and germination potential. Our technology enables breeders and producers to drastically improve seed quality, increase yields, and ensure a more secure and sustainable food future. Join us as we transform the global seed and grain supply chain.
About the Role
We are seeking a seasoned Senior Python Backend Developer: Team Lead to lead backend development, integrate computer vision capabilities into our architecture, and ensure our cloud systems are high-performing, reliable, and secure.
Key Responsibilities
- Backend Architecture & API Design: Architect, build, and maintain highly scalable and secure backend services and APIs using Python web frameworks (preferably Django).
- Computer Vision Integration: Integrate CV models/pipelines into core backend workflows, optimizing for speed, memory usage, and throughput.
- Database & Data Modeling: Design, query, and optimize relational SQL databases to ensure fast query performance, data integrity, and high availability.
- Cloud Infrastructure (AWS): Deploy, scale, and manage backend services on AWS, ensuring secure deployment pipelines and resource efficiency.
- Collaboration & Quality: Lead technical design discussions, write clean and well-tested code, conduct code reviews, and mentor junior/mid-level team members.
- MLOps Integration (Advantage): Assist in streamlining ML model deployment, tracking, monitoring, and pipeline automation to bridge the gap between AI research and production backend code.
Requirements
Must-Have Skills & Experience:
- Experience: 10+ years of professional software development experience with proven expertise in Python.
- Backend Development: Hands-on experience building backend services in Python and deploying computer vision models within backend services.
- Web Frameworks: Strong command of Django (preferred) or other modern Python web frameworks (FastAPI, Flask) for building complex web services and RESTful APIs.
- Database Management: Strong fluency with SQL and relational databases (PostgreSQL, MySQL), including schema design, indexing, and query optimization.
- Cloud Platforms: Hands-on experience deploying and managing backend application architectures on AWS.
- Computer Vision: Practical experience working with Computer Vision frameworks (e.g., OpenCV, PyTorch, TensorFlow, PIL).
- Software Engineering Best Practices: Experience applying object-oriented or functional programming concepts in Python, clean architecture, unit testing/integration testing, CI/CD pipelines, and Git workflows.
- Technical Leadership: Experience leading technical design discussions, conducting code reviews, and leading a software engineering team.
Nice-to-Have (Added Advantage):
- Domain Experience: Knowledge of biotechnology or a closely related domain.
- MLOps Experience: Familiarity with MLOps tools and practices for monitoring, versioning, and managing ML models in production environments.
Benefits
What We Offer
- 100% Remote Work: Work from anywhere with a flexible schedule.
- Long-Term Stability: A sustainable, long-term position in a growing engineering team.
- Technical Ownership: High autonomy to make architectural decisions and impact core products directly.
As published by workable
First name, Last name, Email, Headline, Phone, Address, Photo, Education, Experience, Summary, Resume, Cover letter
- Do you have 10 years of proven experience with backend web development in Python? yes / no
- At Seed-X, backend services process continuous streams of high-resolution seed images for real-time analysis. In your previous roles, how have you architected Python backends (like Django or FastAPI) to handle CPU/GPU-heavy image processing without causing API time-outs or crashing web servers? written answer
- Given your 10+ years of experience, could you walk me through a time when a Python application backed by a SQL database faced severe performance issues on AWS? How did you identify whether the bottleneck was in the Python code, the database query, or the AWS infrastructure? written answer
- How have you integrated Computer Vision models (using libraries like OpenCV, PyTorch, or TensorFlow) directly into production Python applications, and what was the biggest performance bottleneck you encountered? written answer
- What is your salary expectation from this role? Please answer in USD per month.