AI Engineer

Location: Remote — USA, Canada, Europe, or Australia

Salary: $115,000–$130,000 USD per year or $95,000–$115,000 CAD per year

Company

hirify.global provides proprietary automotive data, advanced analytics, industry expertise, and workflows that connect insight to action.

What you will do

• Build full-stack components for AI pilots, including backend services, REST APIs, data pipeline connectors, and frontend implementations.
• Integrate applications with Snowflake, internal APIs, cloud platforms, API gateways, and core data infrastructure.
• Develop reusable Power Agents library patterns with tests, documentation, traces, and auditability.
• Build agent tool integrations, evaluation harnesses, and observability instrumentation to verify reliable behavior.
• Work with frontier model APIs, agentic frameworks such as LangGraph and CrewAI, and MCP server integrations.
• Collaborate with the AI Experience Engineer on UI components, backend connections, technical scoping, prototypes, and technology evaluations.

Requirements

• Full-stack engineering fundamentals across backend APIs, cloud-native services, data sources, and functional frontend interfaces.
• Demonstrable experience building with an LLM API and practical understanding of RAG and tool-calling.
• Ability to write clean, well-documented code and learn quickly alongside principal-level engineers.
• Experience or strong interest in AI coding tools and production-oriented AI system development.

Nice to have

• Python and/or TypeScript experience.
• Experience with LangChain, LangGraph, or equivalent agent frameworks.
• Familiarity with Snowflake, BigQuery, vector databases, RAG patterns, or evaluation harnesses.
• Knowledge of tracing, logging, Langfuse, LangSmith, or other observability tools.
• Experience with hirify.global platforms, APIs, data schemas, or product ecosystem.

Culture & Benefits

• Collaborative, innovative, data-grounded environment focused on delivering practical solutions.
• Opportunity to work on AI pilots and contribute reusable engineering patterns used across the organization.
• Exposure to frontier AI application development and production-adjacent delivery.
• Inclusive employment practices and accommodation support during recruitment.