Palantir Foundry Engineer

02 ott - Cagliari
Luxoft

In this role you will design, build, and operationalize AI-powered workflows within Palantir Foundry and AIP to drive tangible business outcomes. You will translate complex needs into scalable technical solutions and collaborate with stakeholders to maximize value from Foundry and AIP. You’ll work on end-to-end delivery, governance, and adoption, shaping how AI-enabled data pipelines and agents support decision-making. This is a hands-on, cross-functional role with a focus on practical impact, responsible AI, and continuous improvement. Join a senior engineering team to scale AI-enabled workflows across business domains and data landscapes.
Design, develop, and maintain scalable Palantir Foundry pipelines, transformations, and applications
Support 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) with data sources, embeddings, vector search, and ontology content
Apply Ontology-Augmented Generation (OAG) for operational decision-making with embedded logic, data,



actions, and relationships
Collaborate with senior engineers on agent design, instructions, and evaluation using AIP features
Capture requirements, design solutions, and deliver working applications with stakeholders
Provide training and support for business teams adopting Foundry and AIP
Ensure solutions meet data quality, governance, and responsible AI standards
Identify opportunities to expand AIP adoption and improve workflow automation
10+ years IT/Data experience
5+ years as Data Platform Engineer/Data Engineer
2+ years Palantir Foundry ecosystem experience
1+ years hands-on Palantir AIP experience (design/deployment of AIP use cases)
Experience grounding agents with RAG, data sources, embeddings, and ontology content
Ontology-Augmented Generation experience for operational decision-making
Collaboration with senior engineers on agent design and evaluation
Strong Python, PySpar

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