This position is listed on behalf of a partner company, who manages all applications and next steps.
Responsibilities
Build full-stack features and components for AI pilots and prototypes, including backend services, REST APIs, data connectors, and frontend implementations.
Develop clean, well-documented code designed for reliable handoff to teams responsible for maintaining operational systems.
Integrate AI applications with cloud platforms, data infrastructure, internal APIs, API gateways, and data sources such as Snowflake.
Follow established API gateway, data access, schema, and integration standards.
Contribute to an internal AI agent library by implementing reusable agent patterns, writing tests, instrumenting traces, and documenting module behavior.
Build and maintain AI agent capabilities, including tool integrations, API connectors, evaluation harnesses, and observability instrumentation.
Develop baseline evaluations that help verify AI agent behavior, reliability, and consistency.
Work with frontier model APIs, agentic frameworks such as LangGraph and CrewAI, and MCP server integrations.
Collaborate closely with AI and product experience engineers to implement frontend components.
Support technical scoping for new initiatives.
Participate in emerging technology evaluations by building proof-of-concept implementations.
Apply observability and testing practices throughout development.
Requirements
Strong full-stack software engineering fundamentals, including backend development, REST APIs, cloud-native service patterns, data integrations, and frontend implementation.
Demonstrated experience building something real with an LLM or AI system, such as an AI agent, RAG pipeline, tool-calling integration, or comparable application.
Genuine curiosity about AI systems.
Practical understanding of RAG, tool calling, LLM APIs, and modern AI application patterns.
Strong ability to write clean, maintainable, well-documented code.
Experience with Python and/or TypeScript is highly valuable.
Familiarity with LangChain, LangGraph, CrewAI, or comparable agent frameworks is an asset.
Experience with Snowflake, BigQuery, or another cloud-based data platform is beneficial.
Understanding of RAG architectures, vector databases such as pgvector, Pinecone, or Weaviate, and basic AI evaluation harnesses is preferred.
Familiarity with AI observability concepts, including traces and logs, and tools such as Langfuse or LangSmith, is an advantage.
Strong collaboration and communication skills.
Candidates must be legally authorized to work in Canada, as employment sponsorship is not provided for this position.
Conditions
Fully remote opportunity within United States.
Starting annual salary range of $115,000–$130,000 USD.
Virtual-first working environment with flexible work arrangements.
Opportunity to work hands-on with modern AI engineering technologies.
Exposure to real-world AI application development, evaluation, observability, and cloud data infrastructure.
Collaborative environment alongside experienced AI and software engineers.
Learning and development opportunities focused on emerging technologies and practical AI engineering.