Senior Forward Deployed AI Engineer
New
N
NewRocketEnterprise AI Software
USA - RemoteFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 5-8 years
- Required Skills
- PythonCloud ComputingJavascriptTypeScriptServiceNowPrompt EngineeringLLM
Requirements
- 5-8 years of experience in software engineering, systems integration, enterprise platforms, workflow automation, or related technical delivery roles.
- Strong engineering foundation with hands-on experience in full-stack development, scripting, APIs, microservices, enterprise integrations, or cloud-native applications.
- Experience building, deploying, or supporting AI/LLM-powered applications, RAG systems, or agentic workflows.
- Proficiency in JavaScript/TypeScript, Python, or similar programming and scripting languages.
- Experience with cloud platforms such as AWS, Microsoft Azure, or Google Cloud.
- Familiarity with modern LLM application concepts including prompt engineering, context windows, vector search, RAG, and function calling.
- Understanding of responsible AI concepts, hallucination mitigation, and secure AI deployment.
- Experience operating in customer-facing engineering, consulting, or professional-services roles.
- Ability to manage ambiguity, prioritize effectively, and travel approximately 25%.
- Strong problem-solving and communication skills for technical and business stakeholders.
Responsibilities
- Deploy, configure, and operationalize agentic AI workflows, AI assistants, and AI-powered automations within client ServiceNow environments and enterprise technology ecosystems.
- Translate customer business requirements, operational processes, and desired outcomes into technical architectures, implementation plans, and production-ready AI solutions.
- Implement and integrate NewRocket Agent Packs, AI accelerators, and workflow solutions into enterprise environments.
- Work directly with customer teams to tailor AI solutions to their operating models, business processes, data sources, security requirements, and user needs.
- Support workshops, discovery sessions, technical working sessions, demonstrations, pilots, and production rollouts.
- Clearly communicate AI capabilities, limitations, tradeoffs, solution behavior, and adoption considerations to technical and business stakeholders.
- Build enterprise AI applications using Claude, the Anthropic API, and other LLM platforms.
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