Forward Deployed AI Engineer (Palantir)
Here is the updated Job Description with Palantir Platform & Ecosystem experience (AIP, Foundry, Ontology) seamlessly integrated across the Overview, Responsibilities, and Qualifications.
Job Description: Forward Deployed AI Engineer
Role Overview
As a Forward Deployed AI Engineer, you will sit at the intersection of AI engineering, product strategy, and enterprise client delivery. Working closely with enterprise partners, you will own the end-to-end strategy, architecture, and deployment of production-grade Generative AI workflows and Ontology-driven applications to address high-stakes real-world challenges.
This role operates much like a hands-on AI startup technical leader—taking concepts from problem decomposition, data integration, and prototyping all the way to robust, scalable field deployment leveraging Palantir platforms (AIP, Foundry).
Core Responsibilities
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Solution Architecture & Platform Delivery: Design, build, optimize, and deploy end-to-end LLM workflows, data pipelines (PySpark/Python), and generative AI tools natively within Palantir AIP (Artificial Intelligence Platform) and Palantir Foundry.
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Ontology-Grounded AI Workflows: Map complex enterprise domain logic into Palantir Ontologies, connecting unstructured LLM tool-calling and agentic reasoning directly to structured operational datasets and downstream actions.
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Client & Business Strategy: Partner directly with technical leads and executive stakeholders to translate complex operational challenges into actionable AI implementations and clear business outcomes.
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Product Feedback Loop: Capture field insights, client requirements, and edge-case operational failures to directly inform and refine internal core AI product platforms, tooling, and reusable Palantir AIP components.
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Iterative Problem Solving: Work in agile, cross-functional teams to rapidly prototype, validate, and scale production-ready AI solutions and custom user interfaces (e.g., AIP Logic, Workshop, Slate).
Key Qualifications
Required Experience & Technical Skills
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Palantir Ecosystem Expertise:
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Proven experience building and deploying applications on Palantir Foundry and/or Palantir AIP.
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Hands-on experience with Palantir Ontology modeling, AIP Logic, Workshop/Slate frontend design, and data transform pipelines.
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Gen AI & LLM Engineering:
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Proven track record of building and deploying solutions utilizing Large Language Models (LLMs), RAG architectures, prompt engineering, and agentic tool-calling frameworks.
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Machine Learning & Evaluation Fundamentals:
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Solid grounding in ML core concepts, including evaluation methodologies (evals), guardrails, model fine-tuning, and problem decomposition.
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Software & Data Engineering Proficiency:
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Strong coding skills in Python (including PySpark / Spark for high-volume data transforms).
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Proficiency in additional languages such as TypeScript/JavaScript, Java, or C++.
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Engineering Background:
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Bachelor’s or Master’s degree (or equivalent practical experience) in Computer Science, Software Engineering, Mathematics, Physics, Machine Learning, or a related technical field.
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Business & Communication Skills:
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Ability to solve business-oriented operational problems rather than academic benchmarks.
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Strong client-facing communication skills to bridge technical architectures with executive decision-makers.
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Willingness to Travel:
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Ability and willingness to travel to client sites as needed (up to 25%).
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Preferred / Bonus Qualifications
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Experience with cloud infrastructure (AWS, Azure, GCP), containerization (Docker, Kubernetes), and DevOps / CI-CD pipelines.
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Official Palantir Certifications (Palantir Foundry Data Engineer, Application Developer, or AIP Specialist).
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Hands-on experience deploying AI systems in high-compliance or complex environments (Federal/Defense, Healthcare, Finance, or Supply Chain).