ServiceNow Lead Forward Deployed Engineer
About The Position
At Deloitte, Forward Deployed Engineers (FDE) don’t just build AI solutions, they help clients turn AI ambition into enterprise-scale impact, pairing leading class engineering with pod-based delivery and vertical expertise. If you thrive at the intersection of product, engineering, problem-solving, and client impact, this role puts you at the forefront of AI transformations. As a ServiceNow Lead Forward Deployed Engineer, 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. You’ll set technical direction, remove delivery blockers, and stay hands-on, designing, reviewing, and debugging systems with the team. You’ll translate engineering trade-offs into clear decisions for client leaders when needed. Your ability to influence decisions at the C-suite level, while maintaining hands-on technical credibility, is what sets you apart. Pods under your leadership may be deployed onshore with clients or in hybrid onshore/offshore configurations, leveraging Deloitte's global delivery capability to maximize speed and scale.
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.
- 5+ years of experience with the ServiceNow platform.
- 1+ years of hands-on experience building and deploying GenAI/LLM-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.
- 1+ years of experience leading project workstreams or 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.
- Ability to obtain and maintain a US government security clearance.
Nice To Haves
- ITIL v3.0 or v4.0 Foundation Certification.
- Active ServiceNow Master Architect Certification.
- Experience with cloud environments, including Amazon Web Services (AWS), Microsoft Azure, and/or Google Cloud, and common platform services including storage, compute, identity and access management (IAM), and networking.
- Experience working directly alongside client technical teams and program stakeholders in fast-paced, ambiguous delivery environments.
- Experience with Spark, Airflow/dbt, streaming, data modeling, feature engineering, experimentation, or model evaluation.
- Experience with machine learning operations (MLOps) or large language model operations (LLMOps), including evaluation frameworks, model monitoring, and prompt management.
- Experience integrating LLM solutions with enterprise systems via application programming interfaces (APIs), microservices, or event-driven architectures.
- Experience operating within hybrid onshore/offshore teams.
- Familiarity with security, privacy, and compliance considerations.
Responsibilities
- Serve as the senior client-facing presence, building trusted advisor relationships as the senior engineering partner for client product, data, and platform leaders.
- 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, information technology 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.
- 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 FDEs.
- Architect and oversee delivery of LLM-enabled applications, including copilots, agentic workflows, assistants, and knowledge search experiences using one or more enterprise AI platforms.
- Set direction for prompt engineering, tool-use patterns, and human-in-the-loop controls.
- Govern end-to-end retrieval-augmented generation (RAG) 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 bars to these standards.
- Review and contribute to production-quality code.
- Guide architecture of data pipelines powering GenAI use cases.
- Enforce strong data management, testing, continuous integration/continuous deployment (CI/CD), logging, versioning, and documentation practices.
- Bring deep familiarity with cloud environments, including Amazon Web Services (AWS), Microsoft Azure, and/or Google Cloud.
Benefits
- Discretionary annual incentive program
- Reasonable accommodations for people with disabilities
- Opportunities to build new skills
- Leadership opportunities
- Mentorship
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What This Job Offers
Job Type
Full-time
Career Level
Senior
