OneOQ builds wafer-scale metalens arrays on fused silica: nano-optics for the collimation and coupling layer of fiber arrays in AI data center co-packaged optics (CPO), silicon photonics, optical interconnect and optical I/O at 1310 nm. Samples targeted Q1... Backed by Techstars.
About the role
Design, build, and operate the AI systems that Operations relies on. The AI Engineer is responsible for the most technically demanding work — advanced algorithms, production agents, and shared frameworks — and delivers reusable infrastructure that enables the rest of the team to work efficiently. Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- Minimum 5 years of software engineering experience, including demonstrated production ownership of AI or ML systems
- Extensive experience with LLM-based systems, including agent frameworks, tool use, evaluations, prompt engineering, and retrieval
- Strong Python engineering skills, with familiarity in at least one of optimization, forecasting, or computer vision
- Experience designing APIs, SDKs, or frameworks consumed by other engineers
- Proven track record operating systems in production, including monitoring, incident response, and cost management
- Skills in: relational database design including table structures, indexes and primary/foreign key fields
More about this role
Design, build, and operate the AI systems that Operations relies on. The AI Engineer is responsible for the most technically demanding work — advanced algorithms, production agents, and shared frameworks — and delivers reusable infrastructure that enables the rest of the team to work efficiently.
- Production AI systems: Develop, deploy, and maintain operations-critical AI systems, including agents, harnesses, tools, and evaluation pipelines. Accountable for reliability, latency, cost, and accuracy.
- Advanced algorithms: Develop numerical optimization, forecasting, computer vision, and anomaly detection capabilities in cases where off-the-shelf AI does not meet the operational requirement.
- Shared frameworks: Develop the code templates, agent skills, and function-calling patterns reused by Forward Deployed Engineers and AI Analysts, enabling consistent and efficient delivery across the team.
- Tooling and prompts: Design, tune, and evaluate purpose-built tools, function calls, and prompt templates.
- Operations-aware user experience: Develop custom user interfaces for operations workflows, designed from user requirements.
- Mentorship: Develop the capabilities of Forward...
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