Top Entry Level Artificial Intelligence Software Engineer Jobs

Build and deploy production backend services, third-party integrations, internal tooling, and voice agents for strategic enterprise customers. Work directly on site with customer technical and business teams, monitoring and optimizing live systems for accuracy, latency, and throughput. Collaborate with research and product teams to extend the platform, provide field feedback, and create reusable solutions. The role involves regular customer-site work, solution scoping, technical problem-solving, and end-to-end ownership of deployed systems.

Build, deploy, operate, and continuously improve secure enterprise reporting and intelligence applications. Develop full-stack solutions using Python, Django or Flask, React, JavaScript, HTML, CSS, and SQL. Manage Azure cloud deployments, CI/CD, monitoring, troubleshooting, code reviews, testing, and application security. Collaborate with Finance, IT, Operations, and business stakeholders to translate requirements into scalable, user-friendly applications and recommend technology improvements.

Embed with customers to design and build end-to-end, production-quality software and LLM workflows. Collaborate on architecture, handle large-scale data and storage, develop cloud and front-end solutions, and own stakeholder relationships while traveling 25–50%.

Develop and deploy EDA/CAD software, automation, and AI-assisted tools to accelerate custom memory IC design workflows. Collaborate with design, layout, verification, and CAD teams to integrate LLMs, generative AI, and automation into verification, modeling, and tape-out flows.

Build product features end-to-end, improve performance and reliability, and create internal tools. Collaborate cross-functionally, work on web UI and backend components, and iterate based on user impact and metrics.

Develop user interfaces for air traffic systems, focusing on map-based applications and real-time data processing.

Build and prototype AI-native interfaces across web and mobile, translating design concepts into responsive, usable code. Develop interaction models for streaming responses, multi-step workflows, feedback, system-state visibility, uncertainty, failure recovery, and user supervision. Collaborate with product, design, and ML teams, contribute to frontend architecture and reusable components, and improve usability, performance, and state management in AI-driven experiences.

Develop and test core software for warehouse automation, inventory orchestration, and order fulfillment. Responsibilities include designing real-time distributed systems, evolving architecture toward microservices, building software with .NET technologies, contributing to multi-threaded applications, writing unit tests and automation frameworks, and collaborating across agile engineering teams.

The job description provides limited role-specific information. The Software Engineer will likely contribute to Symbotic’s core systems and platform services supporting AI-powered robotic warehouse automation, but specific responsibilities and qualifications are not provided.

Own the infrastructure powering Pax Historia’s AI requests across 37+ models and multiple providers. Responsibilities include improving provider reliability, structured outputs, caching, routing, monitoring, cost efficiency, latency, and scalability for billions of monthly tokens. This founding engineer role requires strong fundamentals, attention to detail, data-driven decision-making, and rapid learning. The position is fully in-person in San Francisco and does not involve model training or self-hosted inference.

Build internal production software for research and operations teams, starting with annotation tooling and expanding into researcher planning workflows, dataset browsing, evaluation dashboards, and operational tracking. Own requirements, prioritization, specifications, implementation, deployment, adoption, and iteration. Develop reliable frontend interfaces, backend APIs, data models, dashboards, and cloud services supporting workflows involving people, AI models, and physical operations.