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Deloitte

Audits companies and advises on tax and technology

Lead Palantir Forward Deployed Engineer

AI Application EngineeringConfirmed live in the last 24 hours
Full-timeAtlanta, GA, USA

About the Job

Requirements

  • A bachelor's degree or equivalent in Computer Science, Data Science, or Engineering is required.
  • An active U.S. government security clearance is required.
  • At least 10 years of experience in software engineering, data engineering, data science, or analytics engineering is required.
  • At least 1 year of hands-on experience building and deploying generative AI or large language model-powered solutions in client or production environments is required.
  • At least 1 year of experience with Palantir, including hands-on experience with Foundry, AIP, or Maven, is required.
  • At least 1 year of experience leading project workstreams or engagements and translating business problems into AI solutions is required.
  • At least 1 year of experience building reliable, maintainable, and well-documented code is required.
  • Must be legally authorized to work in the United States without employer sponsorship now or in the future.
  • Ability to travel an average of 50%, based on assigned work and clients.
  • Ability to work independently and collaboratively.
  • Effective written and verbal communication skills.
  • Attention to detail and quality of work product.
  • Ability to build and sustain professional relationships.
  • Ability to lead projects or workstreams.
  • Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment.
  • Ability to meet deadlines.
  • Ability to mentor and provide clear guidance to others.

Responsibilities

  • Serve as the senior client-facing engineering partner, building trusted advisor relationships with client product, data, and platform leaders.
  • Lead executive-level discovery, define success metrics covering quality, latency, cost, adoption, and risk, and develop a phased plan from prototype through production and scaling.
  • Navigate organizational complexity and align executive sponsors, information technology leadership, and business owners around a shared vision.
  • Represent Deloitte's forward-deployed engineering capability in client pursuits, executive briefings, and platform partner engagements, contributing to pipeline development and deal shaping.
  • Lead forward-deployed engineering pods of 2–5 onshore-anchored and offshore-supported engineers, owning execution, resource management, escalations, and overall delivery health.
  • Enforce delivery standards across the pod, including sprint cadences, stakeholder communication plans, risk management, and quality gates.
  • Coordinate multi-pod or multi-workstream engagements, ensuring reliable architecture and a consistent client experience.
  • Mentor and develop junior forward-deployed engineers.
  • Architect and oversee delivery of large language model-enabled applications, including copilots, agentic workflows, assistants, and knowledge search experiences using enterprise AI platforms.
  • Set direction for prompt engineering, tool-use patterns, and human-in-the-loop controls.
  • Govern end-to-end retrieval-augmented generation pipeline design, including ingestion, chunking, embedding, vector retrieval, and hybrid search, ensuring production-grade quality and scalability.
  • Define evaluation frameworks covering quality, hallucination risk, safety, latency, cost, and governance; ensure the pod meets agreed engineering quality standards.
  • Review and contribute to production-quality code.
  • Guide architecture of data pipelines powering generative AI use cases.
  • Enforce strong data management, testing, continuous integration and continuous delivery, logging, versioning, and documentation practices.

Desired Qualifications

  • Experience with cloud environments such as AWS, Azure, or Google Cloud and common platform services including storage, compute, identity and access management, and 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 or dbt, streaming, and data modeling, or a machine learning/data science background involving feature engineering, experimentation, or model evaluation.
  • Experience with machine learning operations or large language model operations practices, including evaluation frameworks, model monitoring, and prompt management.
  • Experience integrating large language model solutions with enterprise systems via application programming interfaces, microservices, or event-driven architectures.
  • Experience operating within hybrid onshore/offshore teams.
  • Familiarity with security, privacy, and compliance considerations.

About the Company

Deloitte

Audits companies and advises on tax and technology

Deloitte audits companies and advises businesses and governments on tax, technology, and risk, and it is one of the Big Four, the world's four largest accounting firms. In 1849 its founder became the first independent auditor of a public company, Britain's Great Western Railway. Its auditors check companies' financial reports for errors and fraud before investors rely on them, while its consultants design strategy, install business software, and defend clients against cyberattacks. Clients pay fees for each audit or project, and each country's Deloitte firm is a separate business owned by its local partners. Deloitte was founded in London in 1845 and is based in New York.

Company size
10,001+
Company stage
Late Stage VC
Total funding
$17.1M
Headquarters
New York, NY
Founded
1845

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