Top Senior Level Python Jobs in Kansas City, MO

As a Senior Front-end Engineer at PixieBrix, you will be responsible for developing high-performance front-ends for their low-code platform, specifically focusing on browser extensions. Your role will involve collaboration with product and customer success teams, creating reusable components, and ensuring code quality through testing and code reviews.

The Network Architect at Constant Contact will design and maintain network infrastructure, create reference architectures, automate tasks, and mentor junior engineers. Responsibilities include deploying solutions, ensuring compliance, troubleshooting issues, and leading projects with minimal supervision.

As a Senior Software Engineer II at Splice, you will define architecture and implement backend services for next-generation products. Your responsibilities include managing complex projects, improving engineering practices, mentoring team members, and ensuring high-quality deliverables while focusing on customer experience.

As a Staff Backend Engineer at Kentik, you will enhance a high-performance data-intensive platform by improving a distributed database and collaborating with cross-functional teams to develop new features and resolve engineering challenges.

The Senior Data Platform Engineer will design and build scalable solutions, manage complex data schemas, and mentor team members. Responsibilities include implementing anti-corruption layers, defensive coding, and developing an event-driven architecture using AWS and Kafka, ensuring platform reliability and performance.

As a Sr. Embedded Algorithms Engineer, you will prototype and implement algorithms for BioIntelliSense products, focusing on vital sign signal extraction from high frequency sensor data. This role involves optimizing algorithms for processor and power constraints, developing testing protocols, and contributing to internal tools for improving algorithm benchmarking and testing capabilities.

As a Lead AI ML Engineer, you will design, develop, and deploy machine learning models and data pipelines. Responsibilities include collaborating with data teams to create scalable solutions, using tools like Databricks and Snowflake, while leveraging SQL and Python for data analysis and model training.