Senior AI Builder

Key Responsibilities

• Design, architect, and ship custom AI-powered internal platforms that serve operational needs across departments including People Operations, Customer Support, Sales, Recruiting, Marketing, Finance, and Executive Operations.
• Translate ambiguous business requirements into technical specifications, system architectures, and shipped software products.
• Own platform development end-to-end, including front-end interfaces, back-end services, data models, third-party integrations, and AI model orchestration.
• Architect multi-stage AI pipelines incorporating large language models, including prompt engineering, tool-call architecture, structured output generation, retrieval-augmented generation, and agentic workflows.
• Conduct model selection across frontier and open-source providers, evaluating on cost, latency, quality, reliability, and performance.
• Design and implement evaluation frameworks for AI features, including test datasets, scoring rubrics, and regression tests.
• Optimize AI systems for cost and performance using lighter models, batching, and caching.
• Partner with department leads to identify inefficiencies, scope solutions, and prioritize high-leverage work.
• Conduct stakeholder interviews, lead requirements-gathering, and translate feedback into iterative improvements.
• Present technical work and outcomes to executive leadership.
• Design and implement integrations with third-party platforms such as HR systems, support ticketing, CRM, ATS, project management tools, and identity providers.
• Maintain and operate platforms in production, including observability, incident response, and iteration based on feedback.
• Document architectural decisions, designs, and procedures; onboard team members.

Requirements

• Bachelor’s or master’s degree in Technology Management, Computer Science, Software Engineering, Information Systems, or related field (or equivalent experience with strong shipped portfolio).
• Demonstrated portfolio of shipped AI-powered applications, with ability to discuss architecture and trade-offs.
• Experience running own business or working at a fast-scaling startup with end-to-end business exposure.
• Proficiency in modern software engineering practices (version control, code review, CI/CD, debugging).
• Hands-on experience with LLM providers, APIs, tool-calling, and structured outputs.
• Experience designing prompt/tool-call architectures, model selection, and optimizing for cost/latency.
• Programming proficiency in Python and TypeScript/JavaScript, with relevant AI frameworks.
• Experience with relational databases, SQL, and modern data tooling.
• Strong communication skills for technical and non-technical audiences.
• Ability to operate autonomously in ambiguous, fast-paced environments.

Preferred Qualifications

• Prior experience as a founder, co-founder, or early team member at a venture-backed, AI-native startup.