Backend Architectural Specialist

We are seeking a highly skilled Backend Software Engineer with expertise in NodeJS and Python, strong DevOps capabilities, and proficiency in leveraging AI tools for accelerated development.

This is an individual contributor role in an early-stage funded startup, requiring high ownership, problem-solving capabilities, and a proactive mindset to build the backbone of our smart farm management platform.

• Design, build, and maintain scalable APIs and microservices using NodeJS and Python
• Architect multi-tenant SaaS systems with proper data isolation and tenant management
• Implement GraphQL and RESTful APIs with focus on performance and reliability
• Build data processing pipelines and real-time systems for agricultural applications

• Set up and manage cloud infrastructure (AWS/GCP/Azure) and deployment automation
• Build and maintain CI/CD pipelines, containerization (Docker/Kubernetes), and monitoring systems
• Drive infrastructure decisions that enable rapid iteration while maintaining system reliability

• Design and optimize database schemas for complex agricultural data (SQL and NoSQL)
• Implement multi-tenant data architecture with proper tenant isolation and security
• Build integrations with IoT devices, external APIs, and third-party services
• Implement data validation, processing pipelines, and API development for frontend consumption

• Leverage AI coding assistants (GitHub Copilot, Claude, etc.) to accelerate development workflows
• Use AI tools for code review, documentation generation, and optimization
• Stay current with AI development tools and advocate for their adoption across the team

• Implement authentication, authorization, and security best practices
• Design tenant-aware security models and access control systems
• Optimize application performance for real-time systems and rural connectivity challenges
• Build resilient systems with proper error handling and recovery mechanisms

• Core Backend Technologies:
  • Strong expertise in NodeJS with experience building production-grade APIs and microservices
  • Proficient in Python for data processing, automation scripts, and agricultural analytics
  • Experience with modern frameworks (Express.js, FastAPI, Django) and architectural patterns
  • Solid understanding of RESTful APIs and GraphQL service design

• DevOps & Infrastructure:
  • Hands-on experience with Docker, Kubernetes, CI/CD pipelines
  • Proficiency with Infrastructure-as-Code tools (Terraform, Ansible, or equivalent)
  • Strong understanding of AWS/GCP/Azure cloud services and deployment automation
  • Experience with monitoring tools (Prometheus, Grafana, ELK stack) and log management

• Database & Data Systems:
  • Experience with SQL databases (PostgreSQL/MySQL) including complex query optimization
  • Familiarity with NoSQL databases (MongoDB, Redis, InfluxDB for time-series data)
  • Understanding of multi-tenant database design patterns and data isolation strategies
  • Experience with database performance tuning and scaling strategies

• AI & Development Tools:
  • Proficiency with AI coding assistants and prompt engineering for development tasks
  • Experience using AI tools for code generation, debugging, and documentation
  • Understanding of how to integrate AI/ML models into backend systems
  • Ability to evaluate and adopt new AI development tools effectively

• Professional Skills:
  • Strong problem-solving and debugging skills with complex distributed systems
  • Ability to work in a fast-paced startup environment with high ownership and accountability
  • Experience with agile development practices and version control (Git)

• Passion for sustainability and alignment with sustainable systems & regenerative agriculture mission
• Experience with SaaS billing systems and subscription management
• Experience with IoT frameworks and protocols (MQTT, LoRaWAN)
• Knowledge of GIS data processing and spatial analysis
• Experience with time-series databases and real-time data streaming
• Understanding of agricultural domain knowledge
• Experience with serverless architectures and event-driven systems
• Knowledge of machine learning deployment and MLOps practices
• Familiarity with edge computing and rural connectivity challenges