4 hours ago
Remote, United KingdomSenior
Responsibilities
- Design, build, deploy, and maintain reusable secure platform capabilities for enterprise AI, machine learning, LLM, RAG, and agentic applications.
- Create cloud architectures, infrastructure patterns, deployment templates, integration components, and engineering standards across AWS, Azure, Google Cloud, and client environments.
- Build secure Anthropic API and Claude integrations with patterns for authentication, prompt and context management, structured outputs, tool use, logging, error handling, and rate limits.
- Establish CI/CD, LLMOps, MLOps, versioning, evaluation, regression testing, deployment automation, monitoring, rollback, and lifecycle-management practices.
- Operate production AI services through incident response, troubleshooting, root-cause analysis, capacity planning, service-level monitoring, and cost optimization.
- Implement containerized, serverless, infrastructure-as-code, identity, access, secrets, security, privacy, compliance, disaster-recovery, and business-continuity capabilities.
- Build data-ingestion, transformation, indexing, retrieval, RAG, vector-search, enterprise-data integration, and data-governance patterns.
- Implement responsible-AI safeguards, observability, tracing, auditability, output validation, guardrails, approval gates, and human-in-the-loop workflows.
- Develop integrations among AI platforms, ServiceNow, enterprise APIs, identity providers, workflow tools, collaboration platforms, and business systems.
- Provide technical guidance, architecture reviews, documentation, playbooks, reusable modules, customer workshops, and technical leadership across engineering and delivery teams.
Requirements
- At least 5 years of experience in platform engineering, cloud engineering, DevOps, software engineering, data engineering, systems integration, or related technical roles.
- Hands-on experience designing and deploying cloud-native applications and services on AWS, Microsoft Azure, and/or Google Cloud Platform.
- Strong experience with CI/CD, Git-based workflows, automated testing, infrastructure as code, and production release processes.
- Experience with Docker, Kubernetes, serverless services, or comparable cloud-native platforms.
- Proficiency in Python, JavaScript/TypeScript, Java, Go, Bash, or similar programming and scripting languages.
- Experience designing and consuming REST APIs, integrating enterprise applications, and implementing authentication and authorization.
- Experience with LLM-powered applications, generative AI services, AI/ML platforms, RAG systems, AI workflow automation, or related technologies.
- Familiarity with prompt and context engineering, token management, embeddings, vector search, RAG, structured outputs, tool use or function calling, evaluations, and model monitoring.
- Experience with logging, metrics, tracing, alerting, observability, and incident management.
- Strong knowledge of cloud security, identity and access management, secrets management, network security, and secure software development.
- Experience with relational and NoSQL databases, data warehouses, object storage, search platforms, or vector databases.
- Strong problem-solving, troubleshooting, communication, and documentation skills, with the ability to work in collaborative, customer-oriented environments.
- Preferred experience includes Claude, the Anthropic API, Anthropic Console, Claude Code, Anthropic Academy or partner training, Model Context Protocol, secure tool integrations, and agent gateways.
- Preferred experience includes LangChain, LangGraph, LlamaIndex, Semantic Kernel, OpenAI Agents SDK, LLM evaluation, prompt and version management, guardrails, AI observability, model gateways, and API gateways.
- Preferred experience includes MLflow, SageMaker, Vertex AI, Azure Machine Learning, Databricks, Kubeflow, vector databases, enterprise search, Terraform, Pulumi, CloudFormation, Bicep, Helm, Argo CD, GitHub Actions, GitLab CI/CD, Azure DevOps, Jenkins, Kubernetes operations, service meshes, API management, event-driven architecture, microservices, and FinOps.
- Preferred experience includes ServiceNow architecture, development, integrations, platform operations, workflow automation, ServiceNow APIs, IntegrationHub, Flow Designer, Virtual Agent, Now Assist, AI Agents, CMDB, knowledge management, consulting, professional services, enterprise architecture, or client-facing technical delivery.
- Bachelor’s degree in Computer Science, Engineering, Information Systems, Data Science, or a related technical discipline, or equivalent relevant professional experience.
Benefits
- The role is based in the UK with location, hybrid, or remote arrangements indicated in the posting; travel depends on client and business needs.
- Relevant certifications in cloud platforms, Kubernetes, DevOps, security, data engineering, ServiceNow, AI/ML, or Anthropic technologies are a plus.
- The role offers the opportunity to build reusable AI platforms, engineering standards, and accelerators supporting NewRocket’s AI Foundry, Anthropic business, and enterprise clients.
Tech Stack
Argo CDAWSAzureBashDatabricksDockerElasticsearchGitHub ActionsGitLab CI/CDGoGoogle Cloud PlatformHelmJavaJavaScriptJenkinsKubernetesMLflowMongoDBPostgreSQLPythonSnowflakeTerraformTypeScript
Categories
About NewRocket
NewRocket is the AI-first Elite partner that activates real value on ServiceNow. As a trusted advisor to enterprise leaders, NewRocket combines industry expertise, human-centered design, and enterprise-grade AI to help organizations navigate change and scale with confidence. With two decades of experience guiding clients to realize the full potential of the ServiceNow AI Platform, NewRocket is among the largest pure-play ServiceNow partners, uniquely focused on enabling enterprises to adopt AI they trust to deliver lasing business value.