Senior Forward Deployed Engineer, ServiceNow
About The Position
At Deloitte, Forward Deployed Engineers help clients turn AI ambitions into enterprise-scale impact by combining engineering, pod-based delivery, and industry expertise. The Senior ServiceNow Forward Deployed Engineer works alongside senior client stakeholders to rapidly prototype and deliver high-impact GenAI-enabled solutions. The role requires building working software, engaging with senior stakeholders and engineers, and delivering measurable business impact. The role embeds with clients to identify business needs and translate high-value GenAI use cases into solutions. It partners with leaders, product owners, architects, and engineers; leads working sessions; delivers AI prototypes; coaches client teams and end users; supports sales and delivery activities; and contributes to mentoring and reusable intellectual capital. The engineer builds AI-enabled solutions, agentic platforms, and workflows across enterprise AI platforms; develops scalable engineering patterns and human-in-the-loop controls; makes architecture decisions balancing quality, safety, latency, cost, and model risk; and delivers production-quality code with strong testing, CI/CD, logging, versioning, and documentation practices. The role also contributes reusable assets and aligns solution design and sprint sizing with senior team members. Deloitte's ServiceNow practice develops strategies and implements systems to build business value and improve performance. It supports clients through system replacement and enterprise transformation, partnering with executives and service owners across HR, IT, Customer, Field Service, and Project Portfolio Management to modernize technology delivery and operating models. Recruiting for this role ends on 10/30/2026.
Requirements
- Bachelor's degree or equivalent in Computer Science, Data Science, or Engineering.
- At least 5 years of experience in software engineering, data engineering, data science, or analytics engineering.
- At least 1 year of hands-on experience building and deploying GenAI/LLM-powered solutions in client or production environments.
- 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 work and clients served.
- At least 8 years of technology implementation experience.
- At least 6 years of ServiceNow implementation experience.
- At least 4 years of team lead experience.
- Proposal, RFP, or sales experience.
- Experience across ServiceNow applications and modules.
- Certified Application Developer (CAD) certification.
- Experience delivering ServiceNow GenAI/agentic solutions, including Now Assist and AI Agents, and familiarity with AI governance tooling such as ServiceNow AI Control Tower.
- Ability to architect scalable, best-practice ServiceNow solutions across Flow Designer, Integration Hub, Service Portal, App Engine, and Now Platform APIs.
- Working knowledge of the ServiceNow roadmap and release cycles, and ability to advise clients on upgrade paths and adoption of new capabilities.
- Demonstrated use of Claude Code to accelerate delivery, including agentic multi-file workstreams, CLAUDE.md project memory, MCP server integrations, and parallel subagents for work such as feature development, test generation, and security review.
- Experience configuring Claude Code hooks to enforce pre- and post-tool quality, compliance, and security guardrails.
- Experience upskilling engineering teams on agentic coding practices, including context management, CLAUDE.md authoring, prompt engineering, subagent orchestration, and MCP integration.
Nice To Haves
- Experience with AWS, Azure, and/or Google Cloud environments and common platform services such as storage, compute, IAM, and networking.
- 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, or data modeling; or an ML/data science background in feature engineering, experimentation, or model evaluation.
- Experience with MLOps/LLMOps practices, including evaluation frameworks, model monitoring, and prompt management.
- Experience integrating LLM solutions with enterprise systems through APIs, microservices, or event-driven architectures.
- Experience operating within hybrid onshore/offshore teams.
- Familiarity with security, privacy, and compliance considerations.
- ServiceNow certification in one or more areas.
- An advanced degree in the area of specialization.
- Module experience across CSM, Creator Workflow, ITxM, HRSD, IRM/GRC, and Source-to-Pay (S2P).
- Experience with GBS on Now, Now Assist, and Creator Workflow.
- ServiceNow SDK experience with Claude and/or GitHub.
- Exposure to Moveworks.
Responsibilities
- Embed with clients to identify business needs and translate high-value GenAI use cases into solutions.
- Partner with leaders, product owners, architects, and engineers to align priorities and delivery.
- Lead working sessions to shape solutions and drive client outcomes.
- Prototype and deliver working AI solutions using industry expertise and emerging capabilities.
- Contribute independently within an FDE pod and mentor newer team members.
- Coach client teams and end users on platform capabilities and AI enablement; build trusted relationships, manage expectations, and support long-term engagement success.
- Support sales and delivery end to end by developing demos and POCs, contributing to proposals and orals, articulating business value, and documenting solutions for client handoff and knowledge transfer.
- Mentor other FDEs through design and code reviews and feedback, and contribute reusable components to intellectual capital.
- Build AI-enabled solutions, agentic platforms, and workflows across enterprise AI platforms.
- Develop scalable AI engineering patterns, tool-use approaches, and human-in-the-loop controls.
- Make architecture decisions that balance quality, safety, latency, cost, and model risk.
- Deliver production-quality code using strong practices in testing, CI/CD, logging, versioning, and documentation.
- Design extensible functionality, support sprint sizing, and align solutions with senior team members.
- Contribute reusable assets including code, prompt libraries, runbooks, and reference implementations.
Benefits
- Discretionary annual incentive program, subject to program rules and applicable factors.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
