This role focuses on owning the end-to-end conversational intelligence layer for a consumer AI travel platform. Responsibilities include transforming LLM capabilities into reliable product behavior across agent loops, prompt architecture, and error recovery. Key requirements include 4+ years of full-stack/backend experience and shipping LLM-powered systems into production.
Key Highlights
Key Responsibilities
Technical Skills Required
Benefits & Perks
Nice to Have
Job Description
# About the company
Our client is a 15-person consumer AI company building an agentic travel platform that understands individual preferences and can plan and book real-time travel experiences. Its product connects conversational intelligence with live inventory from major travel and hospitality brands, allowing users to discover and book verified options in one conversation.
# The role
We are hiring an AI Engineer to own the conversational intelligence layer end to end. You will turn large language model capabilities into reliable product behavior across agent loops, prompt architecture, tool calling, state, memory, streaming, and error recovery. This is a product-focused engineering role for a high-slope builder who ships quickly, diagnoses real failure modes, and takes responsibility for outcomes.
# What you'll do
- Own the full agent architecture, including prompts, tool calling, multi-step reasoning, and streaming
- Productionize conversational state and memory systems that interpret user preferences
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- Build ranking, retrieval, and recommendation experiences that surface useful, personalized results
- Improve multi-turn reliability through refinement loops, error recovery, and graceful degradation
- Design the rendering layer between agent output and the consumer product experience
- Manage provider strategy across leading model vendors, including caching, structured outputs, and fallback behavior
- Define and operate evaluation systems for ranking, retrieval, and agent behavior
- Debug production failure modes and continuously improve quality using evidence from real users
# What we're looking for
- At least four years of experience as a full-stack or backend-leaning software engineer
- Experience shipping LLM-powered ranking, retrieval, or recommendation systems into production
- Hands-on ownership of systems where models interpret user preferences and surface results
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- Real evaluation experience, including defining, running, and iterating on quality metrics
- Comfort across prompting, embeddings, retrieval, memory, preferences, and product-facing agent workflows
- Strong ability to explain specific production failures you diagnosed and corrected
- An AI-native development workflow and a track record of learning and shipping quickly
- Willingness to work regularly from New York City
# Bonus points
- Experience in travel, search relevance, personalization, memory, or consumer recommendations
- Experience at a high-growth startup or top technology company
- Proficiency in TypeScript, with Python also welcome
- Significant side projects involving AI agents or production-grade LLM systems
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- A strong academic or equivalent technical signal
# Compensation and benefits
- Total compensation of $350K-$500K
- Competitive equity
- Direct ownership of a core consumer AI product surface
- Visa transfers, including OPT or H-1B transfers, may be considered case by case
# Location and work model
- Hybrid in New York City
- Full-time position
- Close collaboration with a small, fast-moving team
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