[ASP] Senior AI Engineer with Palantir

Software Mind develops solutions for companies globally, working on transformative projects involving emerging technologies with cross-functional engineering teams.

• Strong commercial experience designing, building, and deploying Agentic AI and multi-agent solutions in production.
• Hands-on experience with Palantir Foundry and Palantir AIP, including data engineering, ontology development, and AI/LLM workflows.
• Strong Python skills and practical experience with agent frameworks such as LangGraph, LangChain, LlamaIndex, or similar.
• Experience building data pipelines and semantic or context layers using structured and unstructured data.
• Hands-on experience with leading LLM providers, RAG architectures, vector databases, and model integration.
• Experience with Git-based development, automated testing, CI/CD pipelines, and DevSecOps practices.
• Understanding of LLM evaluation, AI guardrails, observability, and responsible AI principles.
• Strong English communication skills for collaboration with clients and teams.

Nice to have:

• Experience with advanced Palantir capabilities such as CBAC attribute sets, Data Lineage, Ontology Linter, and Foundry Marketplace.
• Hands-on knowledge of Azure AI Foundry, Databricks, and Databricks Genie.
• Experience designing semantic layers, ontologies, or context spines across Azure, AWS, or GCP.
• Knowledge of LLM model selection, performance optimization, and cost management.
• Background in consulting, rapid prototyping, or upskilling engineering teams.

• Design, build, test, and productionize Agentic AI solutions across the end-to-end lifecycle.
• Develop modular AI agents, tools, and reusable capabilities for multiple business use cases.
• Engineer data pipelines and data products for structured and unstructured data using Palantir Foundry.
• Design and maintain Foundry ontologies, including Object Types, Link Types, Action Types, Interfaces, and Property Sets.
• Build and deploy LLM-powered workflows using Palantir AIP Logic, AIP Automate, and AIP Assist.
• Integrate and evaluate models from OpenAI, Anthropic, and other LLM providers considering quality, security, and cost.
• Implement automated testing, observability, guardrails, and secure CI/CD pipelines supporting production deployments.
• Collaborate with client stakeholders and pod members, sharing Palantir expertise and upskilling other engineers.