AI Engineer

WITHIN•New York, NY

6h•$145,057 - $296,054•Hybrid

About The Position

We are seeking an exceptional AI Engineer to join our growing team and take a leading role in building and evolving our internal AI-powered agent platform used across the organization. In this role, you will design, build, and improve AI-powered applications that integrate large language models (LLMs) with internal tools, SQL databases, advertising APIs (Google Ads, Meta), and stateful code execution environments. You will play a critical role in improving reliability, context orchestration, evaluation maturity, and expanding Rai into document and workflow automation use cases. Your work will directly impact 200–500 employees and potentially clients, making AI a core productivity multiplier across the organization.

Requirements

Strong programming skills in Python with experience building production systems.
Experience building applications powered by LLM APIs (OpenAI, Anthropic, Vertex AI, etc.).
Deep understanding of: Context windows and token limits Multi-turn conversation behavior Tool/function calling Structured outputs (JSON schema) Prompt design and failure modes
Experience integrating external APIs into production systems.
Proficiency in SQL.
Experience working with cloud platforms (GCP, AWS, or Azure).
Strong problem-solving skills and ability to debug complex system behavior.
Excellent communication and cross-functional collaboration skills.
Required knowledge of: Python SQL Cloud Platforms (GCP, AWS, Azure) LLMs / AI APIs Git / GitHub

Nice To Haves

Experience designing evaluation frameworks for LLM-powered systems.
Understanding of embeddings, vector search, and RAG architectures.
Experience building agent or multi-agent workflows.
Experience with stateful execution environments or sandboxed code execution.
Experience with document automation (Google Docs, Slides, PDFs).
Experience building internal developer tools or productivity platforms.
TypeScript.
Data Warehouses (BigQuery, Snowflake, Redshift)
Data Transformation (dbt)
Semantic Layers (Cube, Looker, dbt Metrics)
TypeScript

Responsibilities

LLM Application Development Design, build, and maintain AI-powered applications leveraging LLM APIs, tool calling, and structured outputs.
Agent & Tool Orchestration Develop and improve agent architectures that integrate tools such as SQL execution, Python code execution, and marketing platform APIs through MCP-style integrations.
Context & Memory Management Design and refine multi-turn context handling, session memory strategies, and prompt structures to improve response reliability and reduce hallucinations.
Reliability & Guardrails Implement safeguards for tool execution, SQL queries, and code execution. Improve retry logic, structured validation, and hallucination mitigation strategies.
Evaluation & Quality Assurance Contribute to building structured evaluation frameworks for LLM-powered systems, including multi-turn testing, regression testing, and task-based success metrics.
Product Expansion Support expansion of Rai into document generation, tables, slide decks, and potential Google Workspace integrations.
Collaboration Work closely with Machine Learning Engineers, Product Managers, and Full-Stack Engineers to ensure AI systems are robust, maintainable, and aligned with business goals.
Continuous Innovation Stay current with advances in LLM systems, agent architectures, and applied AI tooling to continuously improve Rai’s capabilities.