Forward Deployed AI Engineer

NewRocket

19h•Remote

About The Position

NewRocket is seeking a Forward Deployed AI Engineer to join the AI Foundry team and work directly with customers to deploy and operationalize AI-powered workflow solutions. This role blends full-stack engineering, AI implementation, and client-facing solution delivery. Forward Deployed AI Engineers partner closely with business consultants, product teams, and customer stakeholders to translate real-world problems into deployable AI-driven solutions. You will help customers implement agentic AI workflows, intelligent automations, and AI-powered integrations within ServiceNow and enterprise ecosystems, while also contributing to the evolution of NewRocket’s AI platforms, accelerators, and intellectual property, including the NewRocket Intelligence Platform, Value Realization Dashboard, and Data Intelligence Platform. This role requires strong engineering skills, curiosity about emerging AI technologies, and the ability to operate effectively in fast-moving customer environments.

Requirements

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.

Nice To Haves

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.

Responsibilities

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.
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.
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.
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
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.
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.
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.