> Markdown version of [/jobs/ext/240281-python-engineer-7](https://www.wearedevelopers.com/jobs/ext/240281-python-engineer-7). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Python Engineer-7 - **Company:** Realign Llc - **Location:** Alpharetta, GA, United States - **Experience:** Expert - **Salary:** $121,000.0 - **Contract:** Permanent contract - **Skills:** Multitier Architecture, Application Programming Interfaces (APIs), Agile Methodology, Artificial Intelligence, Amazon Web Services, Confluence, JIRA, Microsoft Azure, Configuration Management, Code Review, Continuous Integration, DevOps, Python (Programming Language), Machine Learning, Performance Tuning, Tensorflow, Management of Software Versions, Pytorch, Delivery Pipeline, Jupyter, Pytest, Containerization, Scikit Learn, Solid Principles, Kubernetes, Xgboost, Free and Open-Source Software, Code Inspection, Machine Learning Operations, Software Version Control, Docker - **Published:** May 19, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=0c5bbeb36eceb16a ## About the Role * 7+ years of professional Python development experience. * Strong experience building, maintaining and distributing Python libraries or SDKs used by other developers. * Solid understanding of AI/ML workflows: training, validation, inference, and deployment. * Hands-on experience with notebooks (Jupyter/Colab) and designing APIs optimized for interactive usage. * Experience with packaging and releasing Python libraries: * setuptools, poetry, or pip * Semantic versioning * PyPI or internal package registries * Strong knowledge of software design principles (SOLID, clean architecture). * Experience with testing frameworks such as pytest. * Familiarity with CI/CD pipelines and automated releases. * Excellent communication skills and ability to work cross-functionally. Preferred / Nice to Have * Experience with ML frameworks such as TensorFlow, PyTorch, Scikit-learn, or XGBoost. * MLOps experience: model versioning, feature stores, model registries, and monitoring. * Experience deploying models to cloud platforms (AWS, GCP, or Azure). * Familiarity with containerization and orchestration (Docker, Kubernetes). * Experience designing developer-first APIs and SDK usability patterns. * Open-source contributions or publicly available Python packages. ## Description * Design, develop, and maintain Python SDKs that abstract and simplify AI/ML model training, evaluation, and deployment workflows. * Build SDKs optimized for notebook-based development (Jupyter, Colab, VS Code) with excellent usability and documentation. * Implement clean, modular, and extensible APIs to support multiple model types and frameworks. * Package and release SDKs using best practices (versioning, dependency management, backward compatibility). * Ensure SDKs are production-ready, supporting deployment, inference, monitoring hooks, and configuration management. * Collaborate closely with Data Scientists, ML Engineers, and MLOps teams to translate requirements into robust SDK features. * Write comprehensive unit, integration, and contract tests to ensure reliability and stability. * Create and maintain developer documentation, examples, and notebooks. * Enforce software engineering best practices: code reviews, CI/CD, linting, and performance optimization. * Own the end-to-end lifecycle of SDKs-from design and development to release and maintenance. Generic Managerial Skills: Common Focus Areas: * Serve as a liaison to coordinate with cross-functional teams and provide regular updates to technology and business stakeholders * Identify, mitigate and resolve technical issues and project risks * Ensure project meets specifications and quality standards * Proficient in Agile methodology and tools - Jira, Confluence etc. * Critical analytical and problem-solving skills ## Related Videos - [pytest: Simple, rapid and fun testing with Python](https://www.wearedevelopers.com/videos/213-pytest-simple-rapid-and-fun-testing-with-python) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Improving quality with Agentic AI with Rovo Dev and Xray](https://www.wearedevelopers.com/videos/2005-improving-quality-with-agentic-ai-with-rovo-dev-and-xray) - [Introduction to Azure Machine Learning](https://www.wearedevelopers.com/videos/368-introduction-to-azure-machine-learning) - [Automagic Configuration in Python](https://www.wearedevelopers.com/videos/363-automagic-configuration-in-python) - [Docker build without Docker](https://www.wearedevelopers.com/videos/100114-docker-build-without-docker) ## Related Articles - [The 13 Best Python Libraries for Developers in 2025](https://www.wearedevelopers.com/magazine/371-the-13-best-python-libraries-for-developers-in-2025) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [MLops – Deploying, Maintaining And Evolving Machine Learning Models in Production](https://www.wearedevelopers.com/magazine/115-mlops-deploying-maintaining-and-evolving-machine-learning-models-in-production)