AI Engineer
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Role details
Tech stack
Job description
We’re partnering with a rapidly scaling AI company developing intelligent systems that automate sophisticated, high-impact workflows for enterprise organizations. This role sits at the core of the company’s AI engineering efforts, with a focus on agent infrastructure, LLM systems, model orchestration, evaluation, and production-grade AI applications.
You’ll operate across applied AI research and software engineering, taking new advances in foundation models and agent technology and transforming them into dependable products that solve real-world customer problems.
What You’ll Do
- Architect and maintain the infrastructure powering AI agents, including tool execution, computer interaction, state, memory, and workflow coordination.
- Build agent systems capable of reasoning through and executing complex, multi-stage business processes.
- Develop model orchestration and routing systems that dynamically determine the best model or strategy for a given task.
- Create an adaptable AI infrastructure layer that can support multiple model providers and rapidly changing foundation-model capabilities.
- Design evaluation pipelines that continuously measure agent quality, reliability, and performance while catching regressions before deployment.
- Establish benchmarks and testing methodologies for complex, open-ended agent workflows that cannot be evaluated effectively through conventional methods.
- Convert advances in LLMs, agent frameworks, tool use, and computer-use technology into scalable production capabilities.
- Rapidly prototype and iterate across prompting, retrieval, fine-tuning, model selection, and agent design to improve outcomes.
- Influence architecture, engineering practices, and the broader technical roadmap as the organization scales.
- Contribute to building and expanding a high-performing AI engineering team., * Significant ownership, autonomy, and opportunity to influence the technical direction of a rapidly growing AI company
Requirements
- Strong foundations in computer science, with a Bachelor’s, Master’s, or PhD in Computer Science, Electrical Engineering, or a related technical discipline from a strong academic institution preferred.
- Proven experience developing and deploying LLM-based products, autonomous agents, or AI-driven automation systems.
- Strong knowledge of agent architectures, LLM APIs, tool calling, retrieval systems, prompting techniques, model selection, and orchestration.
- Experience taking experimental or research-oriented AI concepts and engineering them into robust, production-quality systems.
- Strong software engineering skills and the ability to work effectively in a fast-moving, technically ambitious environment.
- Comfortable experimenting quickly, measuring results, and iterating based on empirical performance.
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Prepare application
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