Enterprise Palantir Solutions Architect - iDEA by Lear

About the role

The Enterprise Palantir Solution Architect at Lear is responsible for leading the design, development, and production readiness of Palantir Foundry and AIP initiatives. This role requires a strong foundation in enterprise IT architecture, Palantir platform knowledge, and a deep understanding of data and AI patterns.

Responsibilities

• Palantir Platform Architecture
• Serve as Lear’s enterprise authority for Palantir Foundry and AIP, including Ontology, Object Types, Transformations, Feature Sets, AIP Agents, Solution Designer, and developer tooling.
• Stay current on Palantir platform releases, including AI FDE, AI Pilot, AIP enhancements, compute changes, and emerging Foundry capabilities.
• Design scalable, well-patterned data and AI solutions that leverage the strengths of Foundry and AIP.
• Solution Design & Architecture Governance
• Lead the end-to-end architecture of solutions — from data ingestion and harmonization to AI/analytics workflows, application experiences, and data delivery endpoints.
• Provide architectural guidance on internal and external integrations, including APIs, event-driven pipelines, data exchanges, partner integrations, and secure data products.
• Facilitate architecture reviews, solution documentation, and alignment with Lear’s enterprise architecture principles.
• Security, Identity, and Access Controls
• Architect secure-by-design solutions using Foundry’s granular permissioning, object-level controls, and lineage-based access patterns.
• Ensure compliance with enterprise security standards, regulatory needs, and global data protection policies.
• Performance, Compute, and Cost Optimization
• Optimize Foundry compute workloads (PySpark, Code Repositories, Pipelines, applications) for performance, elasticity, and cost efficiency.
• Architect scalable infrastructure patterns for AIP agents, LLM-backed workflows, and compute-heavy workloads.
• Data Quality, Reliability & Intelligent Monitoring
• Ensure solutions include data quality monitoring, validation rules, schema controls, and reliability SLAs.
• Design automated or “intelligent” data health monitoring patterns, alerting, lineage tracking, and remediation workflows.
• Collaborate closely with ontology and data engineering teams to ensure semantic consistency and trustworthy data foundations.
• Production Readiness & Operationalization
• Conduct detailed production readiness assessments covering architecture, security, performance, data quality, observability, DR/BCP, and support models.
• Develop reusable components, patterns, accelerators, and templates that increase solution velocity and consistency for all teams.
• Platform Evangelism & Technical Leadership
• Coach teams on Palantir architecture patterns, platform capabilities, performance optimization, and secure workflows.
• Collaborate cross-functionally with engineering, data science, manufacturing, quality, finance, and commercial stakeholders.
• Contribute to platform roadmap discussions and strategic planning as Lear expands its enterprise data and AI ecosystem.

Qualifications

• Bachelor’s in Computer Science, Information Systems, Data Engineering, or related technical field.
• 5+ years of experience in IT architecture, data platforms, or enterprise solution design.
• 3–5+ years of hands-on Palantir Foundry architecture experience, including Ontology, pipelines, transformations, application development, and data modeling.
• Strong working knowledge of Palantir AIP, including agent frameworks, LLM workflows, grounding strategies, and secure prompt design.
• Experience designing end-to-end data architectures (ingestion → harmonization → semantic modeling → delivery).
• Deep understanding of identity, access management, security patterns, logging, and compliance considerations.
• Expertise in documenting and communicating architecture designs and reviewing solutions for alignment and quality.

Preferred Qualifications

• Experience with manufacturing, industrial systems, or supply chain operations (ISA-95, plant hierarchies, OEE, BOM, routings, genealogy).
• Knowledge of MLOps, LLM/RAG patterns, or operational AI systems.
• Architectural certifications (TOGAF, cloud architecture certifications, etc.).
• Experience designing intelligent monitoring, observability, and reliability engineering patterns.