AI Research Engineer - Pi School
Confirmed on the employer's own hiring board on Oct 20, 2026. First seen by Alion on Oct 16, 2026.
About Pi School
Pi School is on a mission to empower businesses and professionals to leverage AI's transformative capabilities. We believe technology should be an enabler, not a barrier, and it should empower individuals and businesses to grow, innovate, and stay connected. We strive for a world where AI and human potential coexist harmoniously, reshaping the way we work, learn, and prosper. Born in 2017 from the expertise of Translated, an industry pioneer with over two decades of leadership in AI + human translation, Pi School has helped over 100 companies integrate AI solutions to improve their operations, enhance decision-making, and achieve sustainable growth.
Pi School remains at the forefront of the ever-evolving AI landscape and collaborates with prominent research centres and organisations worldwide, such as the European Space Agency (ESA) and the European Commission, to harness AI for both cutting-edge research and practical solutions, driving progress in science and beyond. Our approach is founded on purposeful, impactful work, leveraging technology as a force for good.
We are looking for an EO AI Engineer (Agents & Integrations) to work in our office in Rome.
Pi School's AI research team is building EVE (Earth Virtual Expert), an open-source AI platform for Earth Observation, developed for the European Space Agency. We are looking for an engineer at the intersection of EO data engineering and AI-powered agents to help design, build, and integrate EVE's connections to the ESA ecosystem: satellite data catalogues, processing platforms (APEx, EarthCODE), Copernicus services, and geospatial tooling.
Project specifics
- EVE(Earth Virtual Expert) is being developed by Pi School, with support from Mistral AI and Imperative Space, for ESA Phi-lab.
- EVE is evolving from a text-based EO assistant into a multimodal, agentic platform under ESA Phi-lab, serving as Europe's main knowledge nexus between Earth AI models, data, tools, and resources.
- The project is fully open source, with the aim of publishing code, models, and documentation across several public venues (for example GitHub, the Hugging Face Hub, and ESA Phi-lab).
- Core workstreams:
- Agentic framework: tool calling, planning, multi-agent orchestration.
- Multimodal expansion: satellite imagery understanding.
- Community ecosystem: open tool registry for EO.
- ESA platform integrations: APEx, EarthCODE, CDSE.
- Discover more at eve.philab.esa.int.
Responsibilities
You will be part of Pi School's AI Research team full-time, building the agentic layer at the heart of EVE. In this role, you will:
- Design and implement EVE's agent orchestration with LangGraph: planning, tool calling, state and memory management, and multi-agent workflows.
- Build and maintain MCPservers and clients so EVE can use EO tools and services (data catalogues, processing platforms, community tools) through a common interface.
- Implement agent-to-agent communication with A2A, so EVE can delegate to specialised sub-agents and interoperate with agents from other ESA projects and partners.
- Design specialised sub-agents(for example a data-retrieval agent over CDSE) and the routing logic between them.
- Evaluateand improve agent behaviour: tool-use accuracy, task success, robustness, and latency.
- Follow the state of the art in agentic systems and turn promising ideas into working prototypes, open releases, and publications.
- Help the community ecosystem: short tutorials, notebooks, and docs so others can plug tools and agents into EVE.
Requirements
Hands-on experience with:
- LangGraph: building stateful, multi-step or multi-agent applications beyond simple chains.
- Model Context Protocol (MCP): writing MCP servers and/or integrating MCP tools into agents.
- Agent2Agent (A2A) protocol: agent cards, task delegation, and communication between independent agents.
- LLM-based agents and tool-using systems more broadly (function calling, structured outputs, multi-step orchestration).
- Solid Python engineering.
- Excellent proficiency in English.
Bonus points