ServiceNow Senior Forward Deployed Engineer
Deloitte•Arlington, VA
•$155,600 - $306,800•Onsite
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 Senior Forward Deployed Engineer, you will work side by side with senior functional and technical client team members to rapidly prototype and deliver high-impact GenAI-enabled solutions. This requires a highly motivated practitioner who moves with speed and precision, building working software, engaging confidently with senior stakeholders and engineers to bring measurable business impact from day one.
Requirements
- Bachelor's degree (or equivalent) in Computer Science, Data Science or Engineering.
- 6+ years of experience in software engineering, data engineering, data science, or analytics engineering.
- 3+ years of experience with 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/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
- Architecture Excellence Accreditation.
- Active ServiceNow Master Architect Certification.
- 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.
- Experience operating within hybrid onshore/offshore teams.
- Familiarity with security, privacy, and compliance considerations.
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 while mentoring newer team members.
- Coach client teams and end users on platform capabilities and AI enablement, while building trusted relationships, managing expectations, and supporting long-term engagement success.
- Drive end-to-end sales and delivery support by developing demos/POCs, contributing to proposals and orals, articulating business value, and documenting solutions for smooth client handoff and knowledge transfer.
- Strengthen team and organizational impact by mentoring other FDEs through design/code reviews and feedback, while contributing 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.
- Apply 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
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What This Job Offers
Job Type
Full-time
Career Level
Senior
