We are partnering with a fast-growing technology organization specializing in advanced AI solutions that help businesses streamline complex processes and improve operational efficiency. As the company moves beyond initial product development and expands its enterprise deployments, it is investing in the engineering foundations required to support reliable, high-performance AI applications at scale
The organization is looking for a Senior AI Engineer to drive the development of the core systems powering its next generation of intelligent software. This role sits at the intersection of AI engineering, backend architecture, and distributed systems, with a focus on enabling AI applications to interact with external tools, manage complex workflows, and execute sophisticated tasks with consistency and reliability.
Working alongside a lean, highly skilled engineering team, you will play a central role in shaping the technical direction of the platform. You will have the autonomy to make architectural decisions, introduce scalable engineering patterns, and turn emerging AI capabilities into production-ready infrastructure. This position is ideal for an engineer who combines deep systems expertise with practical experience building intelligent, automated software.
Key Responsibilities
Architect and develop core infrastructure that allows AI-powered applications to interact with APIs, retrieve contextual information, manage working state, and execute complex operations.
Build execution frameworks that coordinate language model requests, external tool usage, API integrations, and dependent tasks across sophisticated workflows.
Develop systems for task scheduling, workflow persistence, execution control, and decision management to support increasingly capable AI-driven applications.
Design modular interfaces that enable integration with different foundation models, inference platforms, AI service providers, and emerging technologies.
Establish robust evaluation and validation pipelines to measure model behavior, assess application quality, and identify opportunities for ongoing performance improvement.
Implement end-to-end observability through distributed tracing, structured logging, metrics, and monitoring to identify bottlenecks and improve production reliability.
Qualifications and Experience
Significant professional experience in software engineering, particularly across AI platforms, backend infrastructure, machine learning systems, or distributed computing environments.
Demonstrated success delivering production software that incorporates large language models, intelligent agents, automated decision-making, or AI-assisted workflow execution.
Strong working knowledge of modern LLM ecosystems, including model-serving APIs, structured outputs, function calling, retrieval-augmented generation, agent frameworks, and inference optimization.
Experience evaluating AI development frameworks and infrastructure technologies, with the ability to make pragmatic choices based on performance, reliability, and long-term maintainability.
Bachelor's or advanced degree in Computer Science, Computer Engineering, or a related discipline is preferred; equivalent practical experience is also valuable.
Compensation and Location
Base Salary: $270,000–$325,000 annually, depending on experience and qualifications
Location: San Francisco, California
Work Arrangement: Hybrid
This role offers the opportunity to take meaningful ownership of the infrastructure behind advanced AI products, combining hands-on engineering with architectural leadership. The ideal candidate is comfortable operating across the AI and systems engineering stack and is motivated to transform promising AI capabilities into dependable software that performs at enterprise scale.
