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Forward Deployed AI Engineer-Anthropic-Netherlands/Western Europe
Full-time
Forward Deployed AI Engineer
AI Foundry \| NewRocket
Location: Remote with travel (\~25%)
NewRocket
NewRocket’s partnership with
Anthropic
gives our AI team access to leading-edge Claude technology and positions us at the forefront of enterprise AI adoption. You’ll work directly with clients to turn emerging AI capabilities into practical, scalable business solutions—combining strong engineering skills with a deep understanding of real-world business needs.
Role Overview
NewRocket is seeking a highly skilled
Senior
Forward Deployed AI Engineer
to join the AI Foundry team and work directly with customers to deploy, operationalize, and scale AI-powered workflow solutions.
This role blends full-stack engineering, enterprise integration, generative AI implementation, and client-facing solution delivery. Forward Deployed AI Engineers partner closely with business consultants, product teams, AI/ML engineers, and customer stakeholders to translate real-world business problems into secure, reliable, deployable AI-driven solutions.
As an Anthropic partner/vendor, NewRocket is expanding its capability to design and deliver enterprise solutions using Claude and other leading AI technologies. In this role, you will apply modern LLM engineering practices—including prompt and context engineering, retrieval-augmented generation (RAG), tool use, structured outputs, agentic workflows, model evaluation, and responsible AI controls—to deliver measurable customer value.
You will help customers implement agentic AI workflows, intelligent automations, and AI-powered integrations within ServiceNow and broader enterprise ecosystems. You will also contribute directly to the evolution of NewRocket’s AI platforms, accelerators, and intellectual property, including the
NewRocket Intelligence Platform
Value Realization Dashboard
Data Intelligence Platform
, and reusable
Agent Packs
This role requires strong engineering skills, curiosity about emerging AI technologies, sound judgment regarding responsible AI deployment, and the ability to operate effectively in fast-moving customer environments.
Key Responsibilities
Client Delivery & AI Solution Implementation
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.
Anthropic and Generative AI Engineering
Build enterprise AI applications and workflows using Claude, the Anthropic API, and other LLM platforms as appropriate for the client use case.
Apply effective prompt and context-engineering techniques, including clear instructions, examples, role and task definition, structured inputs, response constraints, and long-context management.
Design and implement AI workflows using structured outputs, tool use/function calling, API integrations, multi-step orchestration, and human-in-the-loop review patterns.
Build retrieval-augmented generation (RAG) solutions that ground AI responses in authorized enterprise data and knowledge sources.
Implement practical techniques to improve reliability and user trust, including citation or source-grounding patterns, validation, confidence thresholds, output schemas, fallback handling, and escalation workflows.
Stay current on Anthropic platform capabilities, Claude model releases, implementation guidance, responsible AI principles, and enterprise deployment best practices.
Complete relevant Anthropic training, partner enablement, and technical education programs as available, and incorporate those practices into NewRocket solution delivery.
Solution Engineering & Prototyping
Build demos, prototypes, and proof-of-concept implementations that validate AI-driven workflows and customer use cases.
Rapidly iterate with customers and internal teams to refine AI-powered solutions based on feedback, performance results, and operational needs.
Support the design and implementation of AI orchestration, LLM integrations, agentic decision models, and workflow automation patterns.
Evaluate when an agentic approach is appropriate versus deterministic automation, traditional workflow logic, search, analytics, or human review.
Develop reusable implementation patterns, solution templates, prompt libraries, integrations, and deployment assets that accelerate future client delivery.
Full-Stack Engineering & Integration
Develop secure integrations between ServiceNow, enterprise systems, APIs, data platforms, and AI services.
Build supporting components such as scripts, microservices, automation logic, integration services, and lightweight user interfaces.
Implement integrations with AI platforms, enterprise APIs, identity systems, document repositories, databases, and structured and unstructured data sources.
Apply sound engineering practices for authentication, authorization, secrets management, access controls, logging, error handling, version control, and documentation.
Design solutions that meet enterprise expectations for security, scalability, maintainability, observability, and production readiness.
AI Quality, Evaluation & Responsible AI
Develop and execute practical evaluation approaches for AI applications, including test cases, representative datasets, success metrics, and regression testing.
Assess AI workflow quality across dimensions such as relevance, accuracy, groundedness, task completion, safety, latency, cost, and user experience.
Implement safeguards for sensitive data, role-based permissions, appropriate data access, prompt injection risks, unsafe tool use, and unintended model behavior.
Establish human-in-the-loop workflows for sensitive, high-impact, low-confidence, or exception-based decisions.
Document AI solution behavior, known limitations, risk controls, governance considerations, and operational support procedures.
Monitor and improve deployed solutions based on user feedback, usage patterns, performance data, incidents, and evolving customer needs.
Product & Platform Contribution
Actively contribute to the development and evoluti
