Senior AI Engineer

About the role

We’re partnering with an innovative AI company building software capable of handling complex, high-value workflows for modern enterprises. The company is investing heavily in the infrastructure required to make AI systems more capable, autonomous, and dependable in production environments.

They are now hiring a Senior AI Engineer to help develop the platform layer supporting the company’s next generation of intelligent applications. This engineer will work across LLM infrastructure, agent execution, model orchestration, evaluation, retrieval, and AI reliability, helping bridge the gap between emerging AI capabilities and robust production software.

This is a highly hands-on position with broad technical ownership. You’ll move between designing foundational systems, testing new approaches, and turning successful experiments into scalable infrastructure used by real customers.

What You’ll Work On

Design and build core infrastructure for AI-driven applications, including agent execution, state management, memory, tools, external integrations, and computer-use capabilities.

Develop systems that enable AI agents to plan, coordinate, and execute complex workflows across multiple steps and tools.

Build intelligent model-routing and orchestration capabilities that select the appropriate model, tool, or execution strategy based on the task and runtime requirements.

Create flexible infrastructure capable of supporting multiple foundation-model providers, APIs, and evolving AI technologies.

Develop observability and evaluation systems for understanding agent behavior, quality, reliability, latency, cost, and production performance.

Establish automated testing frameworks, benchmarks, and datasets for assessing reasoning, tool usage, and multi-step task completion.

Stay current with developments in LLMs, retrieval systems, agent architectures, tool use, and computer-use models, identifying technologies with meaningful potential for the product.

Prototype new AI capabilities across areas such as prompting, retrieval, fine-tuning, model selection, agent architecture, and workflow design.

Own the transition from promising prototypes to reliable, maintainable systems capable of supporting production workloads.

Work closely with senior engineering leadership to shape architectural decisions and determine where the company should invest in its AI platform and infrastructure.

Help establish engineering patterns and technical foundations that allow the AI stack to evolve rapidly without sacrificing reliability or maintainability.

What We’re Looking For

Strong background in computer science, software engineering, or a closely related technical field. A Bachelor’s, Master’s, or PhD in Computer Science, Electrical Engineering, or a comparable discipline is preferred.

Professional experience building and shipping AI-powered products, LLM applications, agent platforms, intelligent automation systems, or other sophisticated AI software.

Strong understanding of LLM-based application systems, including model APIs, tool calling, retrieval, prompting, agent frameworks, orchestration, and model routing.

Experience building within rapidly changing AI environments where models, tooling, and technical approaches are constantly evolving.

Ability to assess new AI techniques critically and determine how they can be translated into practical, production-ready engineering solutions.

Strong systems-thinking and software engineering skills, with experience taking loosely defined technical challenges from initial investigation through implementation.

Comfortable balancing experimentation with production engineering and knowing when to move from exploration into scalable implementation.

High ownership, strong technical judgment, and the ability to operate independently in a fast-paced environment with significant technical ambiguity.

Compensation & Work Environment

Base Salary: $230,000 – $285,000, depending on experience

Location: San Francisco, CA, Hybrid

Impact: High-visibility opportunity to help define the infrastructure, architecture, and engineering practices behind the company’s core AI platform as it scales.

Please apply only if you meet the core technical requirements outlined above.