Artificial Intelligence Engineer

Raydar; New York (NY); Hybrid; USD 350,000 - 500,000; Full time

Benefits offered by this job

Visa transfers possible

Competitive equity

Direct ownership of core product

Job summary

Raydar, a consumer AI startup, is hiring an AI Engineer to own the conversational intelligence layer end to end. You will transform LLM capabilities into reliable product behavior across agent loops, prompt architecture, tool calling, state, memory, streaming, and error recovery.

The role targets production-grade systems for ranking, retrieval, and recommendations, with ownership of agent workflows and evaluation.

Qualifications

• 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.
• 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.

Responsibilities

• Own the full agent architecture, including prompts, tool calling, multi-step reasoning, and streaming
• Productionize conversational state and memory systems that interpret user preferences
• 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

Skills

Full-stack / backend

LLM-powered systems

User preferences modeling

Evaluation metrics

Prompting & embeddings

Production debugging

AI-native workflow

New York City on-site

Tools

TypeScript

Python

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

• 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

• 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

• 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