AI Engineer

We’re working with a high-growth AI company developing intelligent software systems designed to take on sophisticated operational and knowledge-based work for enterprise organizations. The team is expanding its core AI infrastructure and is looking for a Senior AI Systems Engineer to help build the technical foundation behind reliable, production-grade AI applications. This role sits at the intersection of AI infrastructure, LLM systems, agent execution, model orchestration, and evaluation , with ownership spanning experimentation through deployment. You’ll help turn rapidly evolving AI capabilities into dependable systems that can operate in real-world environments. The ideal candidate is equally comfortable thinking about system architecture, experimenting with new AI techniques, and engineering the infrastructure required to make those approaches work at scale. What You’ll Own Architect and implement the underlying systems that power autonomous AI applications, including agent runtimes, execution environments, state, memory, tool connectivity, and computer interaction. Build orchestration layers that allow AI systems to break down and execute complex, multi-stage workflows with minimal human intervention. Develop model selection and routing infrastructure that dynamically determines which models, tools, or strategies should be used for different tasks and operating conditions. Design provider-agnostic abstractions that enable the platform to work across multiple foundation models, APIs, and AI vendors. Establish evaluation infrastructure and monitoring capabilities to measure agent quality, reliability, latency, efficiency, and overall production performance. Create repeatable testing systems, benchmarks, and evaluation methodologies for open-ended reasoning and multi-step agent behavior. Investigate emerging developments across LLMs, agentic systems, retrieval, tool use, and computer-use technologies and determine which can meaningfully improve the platform. Rapidly prototype and validate new approaches involving prompting, retrieval, fine-tuning, model selection, agent design, and orchestration. Translate successful experiments into maintainable, scalable production systems rather than isolated research prototypes. Partner with senior engineers and technical leadership to make architectural decisions, prioritize infrastructure investments, and define the evolution of the company’s AI stack. What You Bring Strong foundations 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. Hands-on experience developing and deploying LLM-powered products, AI agents, intelligent automation platforms, or similarly complex AI systems in production. Deep familiarity with modern LLM application architecture, including model APIs, tool calling, retrieval, prompting, agent frameworks, orchestration, and model routing. Experience operating in fast-moving AI environments where models, infrastructure, and engineering practices evolve rapidly. Ability to evaluate emerging AI techniques from both a research and engineering perspective, separating promising ideas from approaches that are difficult to productionize. Strong engineering judgment and a track record of taking ambiguous technical problems from experimentation through reliable implementation. High level of ownership and comfort working independently in an environment where priorities move quickly and technical challenges are substantial. Compensation & Work Environment Base Salary: $225,000 – $280,000, depending on experience Location: San Francisco, CA — Hybrid Impact: Significant opportunity to influence the architecture and technical direction of the company’s core AI infrastructure as the organization scales. Please apply only if you meet the core technical requirements outlined above. Show more Show less