Senior AI Engineer

About the role

We’re working with a rapidly growing AI company developing intelligent software designed to automate sophisticated, high-impact work for enterprise customers. As the company expands its product capabilities, the engineering organization is building the underlying systems needed to make AI applications more reliable, scalable, and effective in real-world environments.

The team is looking to add a Senior AI Engineer to help architect and build the infrastructure powering its next generation of AI products. This role sits at the intersection of LLM systems, agent infrastructure, model orchestration, retrieval, evaluation, and production reliability.

You’ll have significant ownership over the technical direction of the platform, working across both foundational engineering and emerging AI technologies. The ideal candidate is comfortable experimenting with new approaches while also having the engineering judgment to turn successful ideas into robust systems that can operate at scale.

What You’ll Build

Architect and develop foundational services supporting AI applications, including agent runtimes, state and memory systems, tool execution, integrations, and computer-use functionality.

Build infrastructure that allows AI agents to independently reason through, coordinate, and execute multi-stage workflows.

Develop model and tool orchestration systems that dynamically determine which models, APIs, tools, or execution paths should be used for different workloads.

Create an extensible AI platform capable of integrating multiple foundation models, providers, APIs, and emerging technologies as the ecosystem evolves.

Build monitoring, evaluation, and observability capabilities that provide visibility into agent quality, reliability, latency, cost, and behavior in production.

Design automated evaluation frameworks, testing infrastructure, benchmarks, and datasets to measure reasoning, tool utilization, and successful completion of complex tasks.

Investigate new developments across LLMs, retrieval, agentic systems, model tooling, and computer-use technologies and assess their relevance to the product.

Rapidly prototype new capabilities involving prompting strategies, retrieval techniques, model selection, fine-tuning, agent design, and workflow execution.

Take successful experiments through the full engineering lifecycle, transforming prototypes into scalable, maintainable production infrastructure.

Partner with engineering leadership on major architectural decisions and help determine the company’s long-term AI infrastructure priorities.

Establish technical patterns, abstractions, and engineering standards that enable the AI platform to evolve quickly while remaining dependable and maintainable.

What You Bring

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

Professional experience developing and deploying AI-powered software, LLM applications, agentic systems, intelligent automation products, or similarly complex AI technologies.

Strong familiarity with modern LLM application architectures, including model APIs, function/tool calling, retrieval, prompting, agent frameworks, orchestration, and model selection.

Experience working in fast-moving AI environments where models, frameworks, infrastructure, and best practices change rapidly.

Ability to evaluate emerging AI techniques and translate promising research or technologies into practical engineering systems.

Strong software and systems engineering fundamentals, with a track record of taking ambiguous technical problems from exploration through production implementation.

Comfortable operating across the boundary between research-oriented experimentation and production-grade engineering.

Strong technical ownership and judgment, with the ability to independently drive projects and make architectural decisions in an environment with limited precedent.

Excited by highly technical, greenfield problems and the opportunity to influence the architecture of an evolving AI platform.

Compensation & Location

Base Salary: $235,000 – $290,000, depending on experience

Location: San Francisco, CA, Hybrid

Opportunity: Join a highly technical engineering organization and play a significant role in defining the infrastructure and architecture behind the company’s core AI platform as it scales.

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