Top Entry Level Artificial Intelligence Software Engineer Jobs

Build and maintain the software engineering backbone of Genesis-World, an open-source multi-physics robotics simulation platform. Responsibilities include scalable testing for JIT-compiled systems, deterministic simulation replay, autodiff integration, scene editing, plugin architecture, actuation, local time stepping, event systems, serialization, telemetry, performance improvements, and legacy refactoring. The role also involves code reviews, issue triage, contributor support, and collaboration with compiler and physics teams across GPU and operating-system platforms.

Develop software for an AI-focused advertising network, shaping ad experiences used by millions. Work across the stack, take ownership of meaningful projects, make technical decisions, collaborate with design, product, and data teams, and communicate with technical and non-technical stakeholders in a fast-paced, in-person environment.

Develop high-performance L4 autonomous driving planning algorithms and systems. Responsibilities include optimizing end-to-end model outputs with safety fallbacks, designing redundant low-compute systems, processing road-test data, and improving simulation platforms using real-world driving data. The role requires software engineering, algorithm design, problem modeling, and collaboration skills, with preferred experience in motion planning or robotics.

Lead a software engineering team supporting Unity on an Android-based device ecosystem. Own execution and technical strategy, optimize Unity runtime performance through benchmarking and analysis, collaborate with engine, platform, graphics, product, and external teams, and communicate progress and vision. Manage, mentor, and develop engineering talent while enabling AI-assisted development workflows and platform-specific experiences.

Provides software support for Applied Materials equipment, resolving low-complexity application and systems issues with supervision. Supports customers through a ticketing system, assists field engineers with issue analysis, and develops product knowledge through training and certifications. Reviews software documentation, customer features, and installation or upgrade instructions. Requires strong communication, motivation, teamwork, and the ability to manage priorities independently. The role is full-time, based in Austin, Texas, and involves 20% travel.

Develop and support enterprise RPA solutions, including unattended UiPath robots, workflow automation, API and REST integrations, Office 365 automation, OCR, Document Understanding, and AI Fabric implementations. Responsibilities include technical design, development, robot monitoring and support, customer collaboration, process analysis, documentation, and applying RPA development best practices.

Build frontier AI agents for data science across the full product lifecycle, from identifying product opportunities through implementation and deployment. Projects include AI-searchable indices for data warehouses, notebook interfaces based on Jupyter, and scalable backend infrastructure for on-premise agentic deployments.

Owns end-to-end development and operation of features across multiple products and technology stacks. Responsibilities include UI, APIs, server logic, infrastructure, deployment, testing, observability, documentation, and support. The engineer will build AI-agent infrastructure involving LLM streaming, tool orchestration, sandboxed execution, and security boundaries, while also developing wallet-based web3 authentication and authorization. The role requires independent delivery ownership and strong TypeScript, React, cloud infrastructure, CI/CD, and production operations experience.

Build end-to-end user features under senior guidance: implement REST endpoints in Node.js/TypeScript, microservices in Python, maintain PostgreSQL schemas, process background jobs with QStash/Upstash, deploy to Cloudflare Workers/Pages/R2, write tests, and collaborate with product/design on React UI components.

Build and maintain full-stack product features across frontend and backend, participate in product decisions and customer conversations, anticipate and handle edge cases in automation/migration systems, and contribute to infrastructure/DevOps as needed.