AI Integration Developer / AI Systems Engineer

About the Role We're looking for an AI Integration Developer to design, build, and maintain systems that connect AI models with real-world business tools and data. You'll work on API integrations, build internal dashboards for monitoring AI workflows, implement MCP (Model Context Protocol) connectors, and write production-grade Python code that powers our AI-driven features. This role sits at the intersection of backend engineering and applied AI — you won't be training models from scratch, but you'll be the person who makes AI actually useful inside our products and workflows. Key Responsibilities API Integrations — Design, build, and maintain integrations with third-party and internal APIs (REST/GraphQL), including AI provider APIs (OpenAI, Anthropic, etc.) and business tools (CRM, payment gateways, e-commerce platforms). MCP Connectors — Build and maintain Model Context Protocol (MCP) servers/connectors that allow AI models to securely interact with internal tools, databases, and external services. Dashboards & Monitoring — Develop internal dashboards to visualize AI usage, performance metrics, token/cost tracking, error rates, and system health. Python Development — Write clean, well-tested Python code for backend services, data pipelines, and automation scripts that support AI workflows. Workflow Automation — Identify manual processes that can be automated using AI + API integrations, and build reliable, production-ready solutions. Documentation & Testing — Maintain clear technical documentation and ensure integrations are properly tested and monitored in production. Required Skills Strong proficiency in Python (3+ years hands-on) Experience building and consuming REST/GraphQL APIs Familiarity with AI/LLM APIs (OpenAI, Anthropic Claude, or similar) Understanding of Model Context Protocol (MCP) or willingness to learn it quickly (we'll provide ramp-up support if you have strong API/integration fundamentals) Experience building dashboards (e.g., using frameworks like Streamlit, Plotly Dash, or a JS frontend + API backend) Solid understanding of authentication/authorization patterns (OAuth, API keys, JWT) Experience with databases (SQL and/or NoSQL) Familiarity with Git, version control workflows, and basic CI/CD Nice to Have Experience with webhooks and event-driven architectures Familiarity with Docker and containerized deployments Experience with cloud platforms (AWS/GCP/Azure) Prior experience integrating AI into e-commerce, SaaS, or business automation tools Experience with prompt engineering or working directly with LLM-