Backend Developer II, Python

What you will do

• Design, develop, test, and support backend product capabilities, services, APIs, data pipelines, and workflows within the AIO platform.
• Develop scalable, reliable, and maintainable Python applications and backend services using object-oriented programming, modular architectures, reusable components, and modern software engineering practices.
• Build and maintain REST APIs and service components using Python frameworks such as Flask, Django, FastAPI, or equivalent technologies, enabling integration across product services, databases, optimization engines, and enterprise systems.
• Develop data-processing and algorithm-integration pipelines that transform product and supply chain data into inputs for optimization and analytical models and integrate model outputs back into product workflows.
• Build and maintain comprehensive automated test suites and validation frameworks, including unit, API, integration, regression, end-to-end, performance, scalability, and data-validation testing.
• Develop robust approaches for algorithm and numerical validation, including input/output validation, boundary and edge-case testing, benchmark comparison, convergence validation, regression detection, and computational performance analysis.
• Validate inventory optimization, supply chain planning, and analytical capabilities using representative datasets, scenario-based testing, benchmarking, and data-driven analysis.
• Work with SQL databases, data-access layers, REST interfaces, data transformation frameworks, asynchronous/background processing, and data-intensive backend workflows.
• Analyze and improve application and algorithm performance, including runtime, memory utilization, service performance, computational scalability, and processing of large enterprise datasets.
• Apply engineering practices around code quality, testability, resiliency, observability, error handling, security, scalability, and production readiness throughout the software development lifecycle.
• Contribute to DevOps and continuous delivery practices, including Git-based development, code reviews, automated builds, CI/CD pipelines, quality gates, deployment automation, environment configuration, and release validation.
• Build and support containerized and cloud-native backend services using Docker and Kubernetes, ensuring consistent development, testing, deployment, and production environments.
• Support application operations through logging, monitoring, health checks, diagnostics, performance monitoring, troubleshooting, and root-cause analysis.
• Troubleshoot and resolve complex software defects, integration issues, algorithmic problems, performance bottlenecks, and quality concerns across backend services and optimization workflows.
• Collaborate with product managers, software engineers, applied scientists, and domain experts to translate product, supply chain, and optimization requirements into production-grade software solutions.
• Leverage AI-assisted development tools and agentic engineering workflows for coding, automated test generation, code analysis, debugging, documentation, and engineering automation, while applying appropriate review and quality guardrails.
• Develop domain and technical knowledge across supply chain planning, inventory optimization, mathematical optimization, analytics, and decision intelligence to contribute to product innovation and customer success.

What we are looking for

• Bachelor's or Master's degree in Computer Science, Software Engineering, Information Technology, Data Science, Industrial Engineering, Mathematics, or a related technical field.
• Experience : 4-6 years
• Strong foundation in software engineering, object-oriented programming, data structures, algorithms, software design principles, and problem solving.
• Strong proficiency in Python and experience developing production-quality software.
• Experience developing backend applications, services, and REST APIs using frameworks such as Flask, Django, FastAPI, or equivalent technologies.
• Understanding of API design, HTTP/REST, JSON, service integration, error handling, logging, and application observability.
• Experience with SQL, relational databases, data-access patterns, and data-processing libraries such as pandas and NumPy.
• Strong understanding of software testing and quality engineering, including unit testing, API testing, integration testing, regression testing, mocking, test automation, debugging, and root-cause analysis.
• Familiarity with Python testing tools and frameworks such as pytest, unittest, or equivalent technologies.
• Experience with Git and modern source-control practices, including branching, pull requests, code reviews, and automated quality checks.
• Working knowledge of DevOps and CI/CD practices, including automated build, test, deployment, and release processes.
• Familiarity with CI/CD technologies such as GitHub Actions, Azure DevOps, Jenkins, or equivalent platforms.
• Familiarity with Docker and Kubernetes for packaging, deploying, validating, and troubleshooting backend applications and services.
• General understanding of cloud-native application development, microservices, distributed systems, scalability, resiliency, configuration management, monitoring, and production troubleshooting.
• Exposure to numerical computing, mathematical optimization, operations research, analytics, machine learning, or data-intensive software systems is an advantage.
• Exposure to supply chain planning, inventory optimization, safety stock, service-level optimization, or decision intelligence is a plus.
• Familiarity with AI-assisted software development, coding copilots, agentic development workflows, or engineering automation is an advantage.
• Strong analytical thinking, problem-solving, collaboration, ownership, and communication skills, with the ability to work effectively across software engineering, science, product, and domain teams.

#Intermediate #LI-RJ1 #Fulltime