Find your next AI Engineering role

The Enterprise Agent Evals & Efficiency team at Perplexity focuses on enhancing the capabilities of AI agents to perform real-world tasks across various enterprise connectors, tools, and data sources. The primary objective is to enable agents to select the appropriate tools, utilize relevant context, and execute complex workflows reliably, while minimizing time and computational resources. This role involves end-to-end ownership, from developing realistic enterprise evaluation environments to implementing improvements in the agent harness, tools, and skills. You will create intricate scenarios involving connected systems, data, and permissions to pinpoint agent weaknesses and refine the tools, skills, context, and models they employ. Collaborating with AI Research, Connectors, and Platform teams, you will translate experimental findings into tangible improvements in task success rates, latency, and cost efficiency.

$220k - $405k

d-Matrix is seeking a Principal Test Automation Engineer to define and build AI-enabled automation across the software development lifecycle, from build and CI through testing and release. This role involves setting technical direction for AI-enabled workflow automation, building foundational components like agent harnesses and integrations, and developing evaluation methods to ensure automation effectiveness. You will work hands-on, shipping critical components and collaborating with other engineers to raise the bar for AI adoption in daily engineering tasks. The ideal candidate will have extensive production software engineering experience, strong Python skills, and experience shipping AI-enabled tools in production.

$195k - $285k

Handshake is seeking a Member of Technical Staff to define how frontier coding agents are benchmarked and improved. This is a high-ownership role for researchers who build, partnering with top AI researchers and software engineers to develop new benchmarks, reward and verifier systems, agent-evaluation methodologies, and data-quality techniques focused on AI for Coding. You will tackle core questions in frontier AI progress, including what to measure, how to design effective evaluations, create high-signal feedback, and build actionable data systems. As an early member, you will have significant influence over the team's technical direction, operating culture, and the open-source software, benchmarks, and research products developed.

$200k - $350k

Prime Intellect is building the open superintelligence stack, a full-stack system for post-training AI models at frontier scale. They are developing open-source models for long-horizon tasks and the platform their research team uses to build them. This role involves building Prime Agent, an open-source coding and research agent, and will span product development and underlying agent systems. You will own features end-to-end, from design through deployment and monitoring, shipping at the pace of an early-stage company tackling a critical problem in AI.

$150k - $300k

Ambral Labs is building a platform to help enterprises leverage their historical data to improve AI model performance. The system reconstructs past company workflows into replayable environments, allowing for the evaluation and enhancement of agent behavior through reinforcement learning and other post-training techniques. This enables companies to develop better, more cost-efficient AI models that they own and control, rather than relying on third-party providers. Having graduated from YC and secured significant funding, Ambral Labs is now expanding its founding team.

$165k - $325k