Senior Backend Software Developer

We are seeking a highly skilled professional to join our team as a Backend Engineer. This role requires expertise in NodeJS, Python, and DevOps, with proficiency in leveraging AI tools for accelerated development.

• Key Responsibilities:
• a) Backend Development:
  • 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
• b) DevOps & Infrastructure:
  • 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
• c) Data & Integration:
  • 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
• d) AI-Augmented Development:
  • 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
• e) Security & Performance:
  • 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
  • Required Skills & Qualifications:
  • a) 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
  • b) 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
  • c) 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
  • d) 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
  • e) 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)
  • Nice-to-Have Skills:
  • f) Additional Skills:
    • 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