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Deloitte

Audits companies and advises on tax and technology

ServiceNow Lead Forward Deployed Engineer

AI Application EngineeringConfirmed live in the last 24 hours
Full-timeRosslyn, Arlington, VA, USA

About the Job

Requirements

  • A bachelor's degree or equivalent in Computer Science, Data Science, or Engineering.
  • At least 7 years of experience in software engineering, data engineering, data science, or analytics engineering.
  • At least 5 years of experience with the ServiceNow platform.
  • At least 1 year of hands-on experience building and deploying generative AI or large language model-powered solutions in client or production environments.
  • Active ServiceNow Systems Administrator certification.
  • Active ServiceNow Application Developer certification.
  • Active ServiceNow ITSM Implementation Specialist certification (CIS-ITSM).
  • Active ServiceNow Technical Architect certification.
  • At least 1 year of experience leading project workstreams or engagements and translating business problems into AI solutions.
  • At least 1 year of experience building reliable, maintainable, and well-documented code.
  • Ability to travel an average of 50%, based on the work and clients and industries or sectors served.
  • Ability to obtain and maintain a U.S. government security clearance.

Responsibilities

  • Serve as the senior client-facing engineering partner and build trusted-advisor relationships with client product, data, and platform leaders.
  • Lead executive-level discovery, define success metrics for quality, latency, cost, adoption, and risk, and develop a phased plan from prototype through production and scaling.
  • Align executive sponsors, information technology leadership, and business owners around a shared vision by navigating organizational complexity and influencing stakeholders.
  • 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 pod delivery standards, including sprint cadences, stakeholder communication plans, risk management, and quality gates.
  • Coordinate multi-pod or multi-workstream engagements to ensure 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, and ensure the pod meets agreed engineering quality standards.
  • Review and contribute to production-quality code.
  • Guide the architecture of data pipelines that power generative AI use cases.
  • Enforce data management, testing, continuous integration and continuous deployment, logging, versioning, and documentation practices.
  • Apply familiarity with cloud environments, including Amazon Web Services, Microsoft Azure, and/or Google Cloud.

Desired Qualifications

  • ITIL v3.0 or v4.0 Foundation Certification.
  • Active ServiceNow Master Architect Certification.
  • Experience with cloud environments, including Amazon Web Services, Microsoft Azure, and/or Google Cloud, and common platform services including storage, compute, identity and access management, and networking.
  • Experience working directly alongside client technical teams and program stakeholders in fast-paced, ambiguous delivery environments.
  • Experience with Spark, Airflow or dbt, streaming, data modeling, feature engineering, experimentation, or model evaluation.
  • Experience with machine learning operations or large language model operations, 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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