Mid level Backend Developer

The ideal candidate is a self-motivated, multi-tasker, and demonstrated team-player. You will be a lead developer responsible for the development of new software products and enhancements to existing products. You should excel in working with large-scale applications and frameworks and have outstanding communication and leadership skills. AI/ML pipeline and development skills desirable. Experience of developing and deploying Monolithic Apps, Microservices, SOA, Serverless, Service Mesh, Twelve Factor Apps is essential.

Responsibilities

• Develop, maintain, and optimize backend services that support AI-powered features for our platform.
• Work with relational databases
  (e.g., MySQL, PostgreSQL) and NoSQL databases (e.g., MongoDB, Firebase, InfluxDB) to design scalable and high-performance data models.
• Implement and maintain robust APIs (REST, JSON, SOAP, gRPC) that allow integration of AI-powered insights into the platform, ensuring seamless data flow between the frontend and backend.
• Use version control systems (Git) for efficient code collaboration and repository management, maintaining proper branching, commit, and release strategies.
• Handle complex image processing tasks, including image upload, transformation (resize, crop, watermark, metadata, etc.), and retrieval, leveraging cloud storage solutions.
• Implement and manage security protocols like JWT authentication, ensuring that endpoints are secure and data privacy is maintained.
• Optimize database queries and ensure data consistency using ACID transactions, solving issues like N+1 problem and implementing sharding strategies for scalability.
• Design and implement caching strategies using Redis, Memcached, and CDN for improving performance and reducing latency.
• Manage and optimize system performance through instrumentation, monitoring, and observability, tracking system health and resolving performance bottlenecks.
• Work with cloud-based services to enable scalable image processing services and efficient storage for large datasets.
• Collaborate with AI and data science teams to ensure seamless integration between backend systems and AI models, handling complex data flows and ensuring reliable performance. Involvement in the development of AI/ML workflows and algorithms.
• Build backend systems that scale efficiently, implementing microservices, serverless architectures, and containerization (Docker, Kubernetes).
• Implement best practices for API development, including rate-limiting, versioning, and security.
• Participate in code reviews, providing mentorship to junior developers and ensuring adherence to development best practices such as Test-Driven Development (TDD), Domain-Driven Design (DDD), and CQRS.
• Stay up to date with the latest backend development technologies and trends, bringing new ideas and solutions to the team.
• Writing clean, high-quality, high-performance, maintainable code
• Develop and support software including applications, database integration, interfaces, and new functionality enhancements
• Coordinate cross-functionally to insure project meets business objectives and compliance standards
• Support test and deployment of new products and features
• Participate in code reviews
• Web Servers-Building for Scale, Server sent Events. Containerization vs Virtualization.  Kubernetes , Docker
• Authentication, OAuth, Basic Auth, Token Auth, JWT, OpenID, SAML

Qualifications

• Experience & Technical Skills:
• 4+ years of experience in backend development, preferably in AI, agritech, or data-driven platforms.
• Proficiency in JavaScript ) and experience working with JavaScript-based frameworks.
• Strong knowledge of POSIX systems and terminal usage, including commands like grep, awk, curl, wget, ssh, and others.
• Experience with relational and NoSQL databases (e.g., MongoDB, Firebase, InfluxDB) and an understanding of database scaling techniques, such as sharding and normalization.
• Familiarity with image processing and cloud storage (e.g., AWS S3, Firebase, or other cloud services) for handling large-scale image data.
• Strong understanding of API design (REST, GraphQL, gRPC, SOAP), including authenticationmechanisms like OAuth and JWT.
• Experience with authentication and authorization protocols such as OAuth, SAML, and JWT.
• Knowledge of caching strategies for both client-side (CDN) and server-side (Redis, Memcached).
• Understanding of security practices such as SSL/TLS, OWASP risks, CORS, and hashing algorithms(bcrypt, scrypt, SHA family).
• Expertise in microservices architecture, serverless computing, and the Twelve-Factor App methodology.
• Experience with containerization (Docker), orchestration (Kubernetes), and cloud-native technologies.
• Ability to handle complex process management, threading, and concurrency in distributed systems.
• Familiarity with monitoring tools and techniques for observability, such as logging, metrics, and tracing to identify performance bottlenecks and optimize systems.
• Experience with scalable architecture, handling throttling, backpressure, circuit breakers, and load shifting.

Software Design & Architecture:

• Expertise in Design Patterns (GOF), Domain-Driven Design (DDD), CQRS, Event Sourcing, and other modern software architectural patterns.
• Experience in developing highly available and scalable systems, implementing solutions for high-throughput and low-latency requirements.
• Ability to design systems for graceful degradation, redundancy, and failure recovery to ensure high uptime and reliability.
• Knowledge of Graph Databases, Time Series Databases (e.g., InfluxDB, TimeScale), and real-time data systems (e.g., WebSockets, Server-Sent Events).
• Bachelor's degree in Computer Science (or related field)
• 3+ years of relevant work experience
• Expertise in Object Oriented Design, Database Design, and XML Schema
• Experience with Agile or Scrum software development methodologies
• Ability to multi-task, organize, and prioritize work

Desirable Skills:

• Experience working with AI-powered platforms or data-driven services.
• Familiarity with machine learning APIs and data pipelines.
• Familiarity with AI/ML deployment on the Edge.