Top Senior Level Artificial Intelligence Software Engineer Jobs in Kansas City, MO

Lead frontend product experiences across web and mobile using React/React Native and TypeScript. Design conversational, AI-native financial planning interfaces, define frontend architecture and component systems, and contribute to AI layer, multi-model orchestration, reliability, and observability. Work cross-functionally across backend, infra, analytics, and product in a seed-stage, remote environment to ship fast, user-trusted experiences.

The Technical Architect will design and implement Salesforce Commerce Cloud solutions, oversee back-end development, manage integrations, and mentor junior developers, ensuring project success and adherence to standards.

Lead backend development to scale and harden API infrastructures, implement unit testing playbooks, optimize core algorithms, support migration from Supabase to a robust cloud provider, ensure system reliability and scalability, collaborate with frontend and DevOps, and integrate AI workflows and RPA where applicable.

The Staff Backend Engineer will architect and scale backend systems, lead identity infrastructure, mentor the team, and ensure system reliability for Stack AI's platform.

Design APIs, build scheduling algorithms for GPU utilization, create resource management systems, and collaborate with frontend engineers for AI infrastructure.

As a Senior Software Engineer, you'll lead the Data Platform team, designing and implementing scalable, distributed systems for data ingestion, storage, and processing, while mentoring peers and guiding technical architecture decisions.

Lead the design and development of Pinecone's API and interfaces for AI agents, focusing on automation and observability while collaborating with cross-functional teams.

Lead and grow a data engineering team to ingest and operationalize healthcare data, ensuring quality, governance, and timely client integrations.

The Staff Software Engineer - Cloud leads the design and implementation of scalable cloud systems and ML pipelines, mentoring a team and collaborating across engineering functions.

Lead and grow the data platform team owning ingestion, transformation, and search layers. Drive architecture, reliability, and performance for real-time and batch pipelines ingesting TBs/day. Partner with detection engineering and product teams, hire and mentor backend engineers, set standards for data modeling and integrations, and remain hands-on to deliver scalable telemetry processing and query systems.