Top Artificial Intelligence Software Engineer Jobs

The Oracle Fusion SCM Lead will implement and deliver Oracle SCM solutions, lead SCM workstreams, and ensure compliance with GxP requirements.

As a Forward Deployed Engineer, you'll work with customers to debug integrations and enhance the Tavus platform by building SDKs and prototypes. You'll translate user feedback into product improvements and drive feature adoption.

Lead clients in designing and deploying Microsoft Azure AI solutions. Oversee multiple projects, engage in client discussions, and support sales efforts.

As a Senior Data Engineer at TRI, you will design and build robust data infrastructure and pipelines to support autonomy research and simulation workflows.

Seeking a Senior Peoplesoft Developer with 6-8 years of experience in PeopleTools, integrating external systems, and strong SQL skills.

The Forward Deployed Engineer is customer-facing, responsible for deployments, debugging, configuring systems, and translating customer needs into product feedback. Requires hands-on coding in Python and SQL.

Build and ship major FruitScope OS web application features across the frontend, backend, UI/UX, databases, APIs, and cloud infrastructure. Develop scalable systems that transform agricultural data into actionable insights for farmers. Own product problems end to end, collaborate directly with customers, and rapidly improve solutions based on feedback.

Build and improve web and mobile consumer features end-to-end using React and TypeScript. Own product problems from discovery through production, analyze funnels and user behavior, design and interpret large-scale A/B tests, and use data to improve creator and player acquisition, engagement, and retention. The role combines hands-on frontend engineering, product strategy, analytics, experimentation, and agentic workflow automation.

Lead and develop a small team of Product Engineers while remaining hands-on in architecture, coding, debugging, and technical direction. Partner with Product and Design to define roadmaps, build reusable customer-facing capabilities, and establish quality standards for AI-native products. Own production reliability, security, permissions, latency, cost, observability, and incident follow-up. Recruit and mentor engineers, improve execution across workstreams, and create durable interfaces with platform, simulation, research, and deployment teams.

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.