To design and build intelligent, agent-based systems leveraging Model Context Protocol (MCP) and advanced LLM frameworks. This role focuses on developing autonomous AI agents capable of tool use, memory management, multi-step reasoning, and system orchestration across enterprise environments.

The ideal candidate will architect scalable agentic workflows, integrate APIs and data sources via MCP standards, implement context-aware memory systems, and ensure safe, reliable AI execution. Responsibilities include prompt engineering, tool integration, evaluation frameworks, guardrail implementation, and performance optimization.

Strong experience with LLM ecosystems (e.g., OpenAI APIs), multi-agent architectures, retrieval-augmented generation (RAG), and production-grade deployment is required. Familiarity with AI safety, monitoring, and human-in-the-loop systems is highly preferred.

Experience in agent-based systems leveraging Model Context Protocol (MCP) and advanced LLM frameworks.

Minimum 3 month on the job experience using GitHub Copilot

At least 3 years of native Android development experience.

Strong experience with Jetpack library components

Extremely comfortable with understanding and implementing internet applications with REST services at the backend

Super awesome with Android concepts like fragments, location services, Google Cloud Messaging API, UI transitions, Image processing and multi-threaded communications, among others

Familiarity with continuous integration (Jenkins), application monitoring (Crashlytics and fabric.io), mocking tools (Appium and Apiary), build tool development and enhancements, using unit testing and cucumber tests for functional tests.

Extremely comfortable with understanding and implementing client-side handlers for web services with REST services at the backend

Knowledge of Android Studio and GitHub is a huge plus.

Experience with Cucumber testing framework desired

B.S. or equivalent degree in Computer Science is desired

Airlines experience