Full Stack Engineer

Who you are

• You should be comfortable writing production software across backend and frontend systems, working with data, and learning new technologies as the problem demands. Success requires strong engineering fundamentals, curiosity about rapidly evolving AI systems, and a practical focus on making complex capabilities reliable and easy for others to use
• This role is ideal for someone with strong Python and systems development experience, solid engineering instincts, and a demonstrated ability to take initiative in complex technical environments
• At least 2 years of professional software engineering experience
• Strong production experience with Python
• Experience building full-stack applications, backend services, APIs, developer tools, or platform products
• Experience integrating complex systems and designing maintainable service boundaries and APIs
• Experience with data-intensive applications, data pipelines, analytics workflows, or operational data systems
• Interest in or hands-on experience with LLMs, AI agents, model APIs, retrieval systems, workflow automation, or other applied AI technologies
• Strong software engineering fundamentals, including testing, version control, code review, debugging, security, observability, and maintainable system design
• Ability to work across multiple layers of a technical stack and learn unfamiliar technologies quickly
• Evidence of self-motivated work, strong ownership, and the ability to make progress in ambiguous situations
• Clear written and verbal communication skills, especially in a distributed engineering environment
• Experience building and operating software on cloud platforms

What the job involves

• We’re looking for a Full Stack Engineer, AI Platform to build the internal products and infrastructure that enable teams to create agentic applications
• In this role, you’ll develop full-stack tools, services, APIs, workflows, and platform capabilities used by engineers and product teams building with AI. You may work on developer interfaces, agent orchestration, model and tool integrations, evaluation systems, observability, prompt and context management, reusable components, and deployment workflows
• Build and maintain internal full-stack products that help teams design, develop, test, evaluate, deploy, and operate AI agents and AI-enabled features
• Develop backend services, APIs, SDKs, workflows, and integrations that connect models, tools, enterprise data, and product systems
• Build reusable platform capabilities for agent orchestration, prompt and context management, tool use, human review, and workflow automation
• Develop evaluation, observability, debugging, and quality-control systems that make AI behavior measurable and reliable
• Design secure patterns for accessing data, invoking tools, managing permissions, and applying appropriate AI safety guardrails
• Partner with infrastructure and application engineering teams to understand needs and translate them into durable platform capabilities
• Improve the developer experience through clear abstractions, documentation, examples, templates, and paved paths
• Write maintainable, well-tested code and participate in design reviews, code reviews, debugging, release processes, and production support
• Take ownership of ambiguous problems, identify practical tradeoffs, and drive work from discovery through production adoption
• Stay current with evolving AI engineering practices and apply new approaches thoughtfully rather than adopting technology for its own sake