Jobs · Engineering · New Jersey

Lead Forward Deployed Engineer, Palantir

Deloitte · Morristown, NJ · 3 days ago
HybridEngineering$189k–$373k/yrFull-time

About the role

Recruiting for this role ends on 10/30/2026. As a Lead Palantir FDE, you will serve as the senior practitioner-leader embedded directly with our most strategic clients, leading forward-deployed engineering pods that develop and deploy GenAI solutions into production for Deloitte's most strategic clients.

Responsibilities

  • Set technical direction, remove delivery blockers, and stay hands-on; designing, reviewing, and debugging systems with the team.
  • Translate engineering trade-offs into clear decisions for client leaders when needed.
  • Influence decisions at the C-suite level, while maintaining hands-on technical credibility.
  • Lead executive-level discovery, define success metrics (quality, latency, cost, adoption, risk), and a phased plan from prototype to production and scaling.
  • Navigate organizational complexity and influence to align executive sponsors, IT leadership, and business owners around a shared vision.
  • Represent Deloitte's FDE capability in client pursuits, executive briefings, and platform partner engagements—contributing to pipeline development and deal shaping.
  • Lead FDE pods of 2-5 onshore anchored and offshore supported engineers, owning execution, resource management, escalations and overall delivery health.
  • Coordinate multi-pod or multi-workstream engagements, ensuring reliable architecture and consistent client experience.
  • Mentor and develop junior FDEs.
  • GenAI Solution Development Architect and oversee delivery of LLM-enabled applications including copilots, agentic workflows, assistants, and knowledge search experiences using one or more enterprise AI platforms (see Platform Requirements below).
  • Set direction for prompt engineering, tool-use patterns, and human-in-the-loop controls.
  • Define evaluation frameworks covering quality, hallucination risk, safety, latency, cost, and governance; ensure the pod meets agreed engineering quality bars to these standards.
  • Engineering & Data Foundations
  • Review and contribute to production-quality code.
  • Guide architecture of data pipelines powering GenAI use cases.
  • Enforce strong data management, testing, CI/CD, logging, versioning, and documentation practices.
  • Deep familiarity with cloud environments (AWS, Azure, and/or Google Cloud).

Requirements

  • Bachelor's degree (or equivalent) in Computer Science, Data Science or Engineering.
  • 7+ years of experience in software engineering, data engineering, data science, or analytics engineering.
  • 1+ years of hands-on experience building and deploying GenAI/LLM-powered solutions in client or production environments.
  • 1+ years of experience with Palantir including hands-on experience with one of the following key platforms; Foundry, AIP, Maven.
  • 1+ years of experience leading project workstreams/engagements and translating business problems into AI solutions.
  • 1+ years of experience building reliable, maintainable, and well-documented code.
  • Ability to travel 50%, on average, based on the work you do and the clients and industries/sectors you serve.

Qualifications

  • Limited immigration sponsorship may be available.

Preferred Qualifications

  • Experience with cloud environments (AWS, Azure, and/or Google Cloud) and common platform services (storage, compute, IAM, networking).
  • Demonstrated ability to work directly alongside client technical teams and program stakeholders in fast-paced, ambiguous delivery environments.
  • Data engineering experience with Spark, Airflow/dbt, streaming, data modeling or ML/data science background feature engineering, experimentation or model evaluation.
  • Experience with MLOps/LLMOps practices: evaluation frameworks, model monitoring, and prompt management.
  • Experience integrating LLM solutions with enterprise systems via APIs, microservices, or event-driven architectures.
  • Familiarity with security, privacy, and compliance considerations.

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