Top Artificial Intelligence Software Engineer Jobs

Develop, maintain, and troubleshoot Java-based applications. Write clean, testable code, collaborate with team members, and participate in design and code reviews.

The Senior Full Stack Engineer will develop back-end systems in Python and create front-end applications using JavaScript/TypeScript and React. Responsibilities include owning product features, designing APIs, and optimizing performance within an AI healthcare platform.

As a Senior Full-Stack Engineer at Parambil, you'll design and implement features for an AI-powered legal tech platform, collaborating closely with cross-functional teams and ensuring quality production delivery.

The software engineer will design, build, and iterate on products for business banking and cash management while managing projects end-to-end.

Own and deliver end-to-end full-stack features for a React frontend and Spring Boot backend. Build/version REST APIs, scale microservices on AWS, optimize PostGIS queries, implement real-time UI updates, support on-call incident response, and mentor engineers.

The role involves application design and development focusing on Micro Focus Cobol and Cobol on IBM Mainframe, requiring strong SDLC knowledge.

As a Forward Deployed Engineer, you'll collaborate with Fortune 100 companies to build AI agents, optimize workflows, and improve productivity through innovative engineering solutions.

The Senior Product Engineer will develop a shared technology platform, focusing on full-stack development and AI agents for workflow automation, collaborating directly with end users.

Build and maintain the frontend architecture, design system, and UI testing framework for an agentic AI security product. Create reusable components and agentic UIs, collaborate with cross-functional teams, coach engineers, and ship end-to-end B2B product experiences that make complex security workflows clear and actionable.

Build end-to-end AI-native product features: design backend (APIs, DB), build frontend, deploy and test. Partner with founders, designers, and legal users, use coding agents and MCP servers to scale the platform and ship high-quality ML/LLM-powered workflows.