Sr. Applied AI Engineer

Senior Applied AI Engineer

Location: New York (in-person collaboration expected)

Compensation: Competitive salary + equity

Please note: Candidates must be authorized to work in the United States and able to maintain ongoing employment without dependencies or employer sponsorship now or in the future.

Our client is an early-stage AI platform focused on helping teams understand customer needs at scale by analyzing interviews, internal data, and market signals.

They are a small but rapidly growing engineering team building production AI systems that customers rely on. This role is focused on improving the quality, reliability, and usefulness of AI outputs rather than working on model internals or pure research. You will work directly with founders to build systems that turn qualitative data into clear insights that drive product and go-to-market decisions.

What you’ll work on

• Designing and improving RAG pipelines that operate on interview transcripts, customer integrations, and other unstructured business data
• Building workflows that extract meaningful signals from qualitative inputs such as conversations, documents, and internal communications
• Developing evaluation approaches to improve answer quality, attribution accuracy, and hallucination risk in production systems
• Debugging model behavior, retrieval performance, and prompt/context strategies as data volume and complexity increase
• Integrating AI capabilities into customer-facing product features and shipping improvements based on real usage
• Collaborating closely with founders and engineers to rapidly test ideas and iterate

What we’re looking for

• Experience building and shipping applied AI systems used by real users
• Practical understanding of RAG architecture, retrieval tuning, and prompt/context engineering
• Experience designing or implementing evaluation approaches to measure AI output quality, reliability, and hallucination risk
• Experience working in TypeScript / Node environments and shipping AI features into production applications
• Product mindset — ability to prioritize user value and system reliability over theoretical elegance
• Curiosity about failure modes in AI systems and persistence in improving them
• Ability to work effectively in a small, high-ownership startup environment

Nice to have

• Experience working with qualitative research data or document-heavy systems
• Exposure to agent workflows or multi-step reasoning systems
• Startup experience where engineers own outcomes end-to-end
• Interest in marketing intelligence, research workflows, or customer insight tooling

Why join

• Direct impact on core product architecture and AI quality
• Work closely with technical founders on real product decisions
• High ownership and fast iteration cycles
• Opportunity to shape how applied AI is used in real business workflows
• Competitive compensation and meaningful equity participation