Forward Deployed AI Engineer

Key Responsibilities

• Client Delivery & AI Solution Implementation
• Deploy and configure agentic AI workflows and AI-powered automations within client ServiceNow environments.
• Translate customer business requirements into technical architectures and implementation plans.
• Implement and integrate NewRocket Agent Packs and AI solutions into enterprise environments.
• Work directly with customers to tailor AI solutions to their operational workflows and business processes.
• Solution Engineering & Prototyping
• Build demos, prototypes, and proof-of-concept implementations to validate AI-driven workflows with clients.
• Rapidly iterate solutions with customers to refine AI-powered use cases.
• Support implementation of AI orchestration, LLM integrations, and agentic decision models.
• Full Stack Engineering & Integration
• Develop integrations between ServiceNow, enterprise systems, APIs, and AI services.
• Build supporting components such as scripts, microservices, automation logic, and integration services.
• Implement integrations with AI platforms, APIs, and enterprise data sources.
• Product & Platform Contribution
• Actively contribute to the development and evolution of NewRocket’s AI intellectual property and platforms, including:
• NewRocket Intelligence Platform
• Value Realization Dashboard
• Data Intelligence Platform
• Agent Packs and reusable AI solution accelerators
• Responsibilities include:
• identifying patterns and capabilities discovered in client deployments
• contributing reusable assets and automation components
• providing product feedback that improves platform capabilities
• helping transform successful client implementations into repeatable platform features
• Client Interaction & Technical Consulting
• Participate in workshops, discovery sessions, and technical working sessions with customers.
• Serve as the engineering counterpart to consulting and delivery teams.
• Communicate architecture, system behavior, and technical tradeoffs clearly to stakeholders.
• Systems Integration & Troubleshooting
• Diagnose and resolve technical issues across AI workflows, integrations, and automation pipelines.
• Ensure deployed AI solutions are secure, scalable, and production-ready.
• Optimize deployed systems for performance and reliability.
• Cross-Team Collaboration
• Work closely with:
• Business Process Consultants
• Product Engineering
• Data Engineers
• AI / ML Engineers
• AI Center of Excellence teams
• Contribute to internal playbooks, reusable deployment patterns, and product evolution.

What Success Looks Like (First 6 Months)

Required Qualifications

• 5–8+ years of experience in software engineering, systems integration, enterprise platforms, or automation systems.
• Strong engineering foundation with experience in full-stack development, scripting, or enterprise integrations.
• Experience working with AI / LLM technologies or AI-powered applications.
• Experience operating in client-facing engineering or consulting roles.
• Experience with cloud platforms such as AWS, Azure, or GCP.
• Experience with languages such as:
• JavaScript / TypeScript
• Python
• or similar scripting languages.
• Strong ability to communicate complex technical concepts to both technical and business stakeholders.

Preferred Qualifications

• ServiceNow Experience (Strong Plus)
• Experience with ServiceNow development or workflow automation platforms.
• Familiarity with ServiceNow scripting, APIs, and platform development patterns.
• Understanding of ServiceNow data models, including:
• CMDB
• workflow / task tables
• knowledge management
• integrations with enterprise systems.
• AI & Platform Experience
• Experience building AI prototypes, RAG systems, or agent-based workflows.
• Experience integrating LLM APIs or AI services into enterprise systems.
• Experience with vector databases, embeddings, or semantic retrieval.
• Experience contributing to internal platforms, reusable accelerators, or product capabilities.

Why This Role Matters

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