Palantir Data Solution Architect

We are looking for a seasoned Palantir Data Solution Architect to lead the design and implementation of enterprise-scale data and AI platforms for Insurance/Reinsurance clients. This role will drive Foundry adoption, AIP-powered GenAI solutions, and intelligent chatbot ecosystems to enable automation, decision intelligence, and regulatory-compliant data platforms. Responsibilities Design and deploy data pipelines, Ontology models and data workflows in Foundry Enable end-to-end data lifecycle management from ingestion through transformation to consumption Implement data lineage, governance and auditability aligned with BFSI compliance Architect AI applications using Palantir AIP, including agents for underwriting, claims and risk analysis as well as intelligent decision-support systems Build RAG-based solutions integrating structured and unstructured BFSI data Integrate external LLMs such as Azure OpenAI and GPT securely within enterprise systems Design domain-aware chatbots, assistants and orchestration interfaces for claims processing, policy servicing and regulatory insights Leverage LangChain/LangGraph and AIP for multi-agent workflows and contextual responses Build scalable pipelines using Spark, Databricks and Delta Lake across batch and real-time architectures Integrate Foundry with core BFSI systems including Policy Admin, CRM, Risk and Finance Lead end-to-end solution architecture and platform design, define best practices, reusable frameworks and accelerators Mentor engineering teams and drive architecture governance Ensure adherence to BFSI regulations including GDPR and PII audit controls, and implement role-based access control, data security and monitoring Requirements 13 to 18 years of experience in Data Software Engineering Expertise in Palantir Foundry including Ontology, Pipelines, Workshop, Quiver, Code Repositories, alongside AIP and Apollo Knowledge of GenAI concepts including LLMs, RAG and embeddings Skills in prompt engineering, multi-agent AI architectures and ML flow model lifecycle Proficiency in Data Engineering including Spark, SQL and Databricks Competency in ETL/ELT design Proficiency in Python, with SQL and Scala/Java preferred Understanding of distributed systems, cloud platforms and API-driven design Strong communication and stakeholder management skills with the ability to drive technical discussions Analytical, problem-solving mindset that is autonomous, detail-oriented and collaborative Nice to have Background in Insurance/Reinsurance domain covering Claims, Underwriting and Premium Familiarity with Policy, Treaty data and related domain expertise