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
