AI Integrations Backend Engineer
Pear
Wood Wide AI is seeking an AI Integrations Backend Engineer to connect their numeric intelligence engine with LLM agents and orchestration frameworks. The role involves designing backend APIs, developing microservices, and ensuring seamless integration for AI builders and enterprises.
Qualification
- 1-3 years of backend engineering experience with Python, FastAPI, or Flask.
- Experience designing API-first microservices and integrating with AI or ML systems.
- Skilled in managing scalable data pipelines and storage solutions using Postgres, Redis, and Kafka.
- Familiarity with Docker, GitHub Actions, and cloud providers like GCP and AWS.
- Strong understanding of REST/gRPC design and CI/CD practices.
- Familiarity with LLM tool-calling APIs.
Responsibility
- Design and build core backend APIs using Python (FastAPI) for numeric intelligence functions.
- Integrate the engine with LLM agents and tool-calling interfaces for structured reasoning.
- Develop microservices and a Model Context Protocol (MCP) server for processing tabular or time-series data.
- Orchestrate agentic workflows using frameworks like Vercel AI SDK and LangGraph.
- Build and maintain a Python SDK with developer-friendly abstractions.
- Develop data connectors for environments such as Databricks, Snowflake, and Postgres.
- Implement authentication, rate limiting, and structured logging for production operations.
- Containerize and deploy microservices using Docker and cloud services.
