Senior Lead Software Developer (Remote)

Position Overview: The Lead Software Architect - Python & Data Engineering is a senior technical leadership role responsible for designing and owning end-to-end architecture for data-intensive, AI/ML, and analytics platforms, while mentoring developers and ensuring technical excellence across the organization. Key Responsibilities: Design end-to-end software architecture for data-intensive applications, AI/ML pipelines, and analytics platformsEvaluate trade-offs between competing technical approaches Define data models, API approach, and integration patterns across systems Create technical specifications and architecture documentation Lead by example through production-grade Python code and mentor developers on engineering fundamentals Conduct design and code reviews focused on architectural soundness Establish engineering standards, coding practices, and design patterns for the team Translate business requirements into technical architecture Collaborate with data scientists, analysts, and other teams to design integrated solutions Whiteboard and defend system design and architectural choices Take responsibility for system performance, reliability, and maintainability Identify and resolve architectural bottlenecks proactively Required Skills:  8+ years of experience in software architecture and development  Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field Strong foundations in data structures, algorithms, and computational complexity Experience in system design for scale, including caching strategies, load balancing, and asynchronous processing  6+ years of Python development experience Deep knowledge of Django, Flask, or FastAPI Expert understanding of Python internals including GIL and memory management Experience with RESTful API design and event-driven architectures (Kafka, RabbitMQ) Proficiency in data processing frameworks such as Pandas, Apache Spark, and Airflow Strong SQL optimization and database design experience (PostgreSQL, MySQL, MongoDB)  Experience with AWS, GCP, or Azure cloud platforms Knowledge of containerization (Docker) and orchestration (Kubernetes) Hands-on experience designing CI/CD pipelines Preferred (Bonus) Skills: Experience deploying ML models to production (MLOps, model serving, monitoring) Understanding of ML system design including feature stores and model versioning Familiarity with ML frameworks such as scikit-learn, TensorFlow, and PyTorch  Open-source contributions or technical blogging demonstrating architectural depth Experience with modern front-end frameworks for full-stack perspective