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A leading technology consulting firm in Italy is seeking an experienced Palantir Foundry & AIP Engineer to work on AI-powered workflows and applications. The ideal candidate should possess over 10 years of experience in Data and AI Engineering, and at least 2 years with the Palantir Foundry ecosystem. Responsibilities include designing and maintaining scalable data pipelines, supporting AIP use cases, and ensuring high quality and governance standards for AI solutions. This role offers opportunities for professional growth in a flexible and dynamic environment.
We are seeking a Palantir Foundry & AIP Engineer with hands‑on experience across the full Foundry ecosystem and Palantir's Artificial Intelligence Platform (AIP). This role goes beyond data engineering: you will design, build, and operationalize AI‑powered workflows, agents, and applications that drive tangible business outcomes. The ideal candidate is a self‑starter, able to translate complex business needs into scalable technical solutions, and confident working directly with stakeholders to maximize the value of Foundry and AIP.
Data & Workflow Engineering: Design, develop, and maintain scalable pipelines, transformations, and applications within Palantir Foundry.
Support the design and deployment of AIP use cases such as copilots, retrieval workflows, and decision‑support agents.
Ground agents and logic flows using RAG (retrieval‑augmented generation) by connecting to relevant data sources, embedding / vector search, ontology content.
Use Ontology‑Augmented Generation (OAG) when needed: operational decision making where logic, data, actions and relationships are embedded in the Ontology.
Collaborate with senior engineers on agent design, instructions, and evaluation using AIP's native features.
End‑to‑End Delivery: Work with stakeholders to capture requirements, design solutions, and deliver working applications.
User Engagement: Provide training and support for business teams adopting Foundry and AIP.
Governance & Trust: Ensure solutions meet standards for data quality, governance, and responsible use of AI.
Continuous Improvement: Identify opportunities to expand AIP adoption and improve workflow automation.
Meetings for knowledge sharing, celebrations, and brainstorming: your ideas count!