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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in deploying and operationalizing AI workflows and solutions, with a strong focus on integrating enterprise systems and APIs. Proficient in full-stack development and cloud platforms, ensuring secure and efficient AI applications tailored to customer needs.
Highest-signal resume keywords
AI Workflow DeploymentFull-Stack DevelopmentAPI IntegrationCloud Platform ExperiencePrompt Engineering
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
JavaScriptTypeScriptPythonMicroservicesScriptingAI/LLM ApplicationsWorkflow AutomationEnterprise IntegrationsRAG SystemsData Platforms
Soft Skills
Customer-Facing EngineeringConsultingTechnical ImplementationProblem-SolvingPrioritization
Tools & Technologies
ServiceNowAWSMicrosoft AzureGoogle CloudAnthropic APIDockerCI/CDSQLGitInfrastructure-as-Code
Industry Keywords
Banking SystemsEnterprise PlatformsAI SafetySensitive-Data HandlingResponsible AI
Tech Stack
Tools & technologiesAWSAzureCloudDockerJavaScriptMicroservicesPythonServiceNowSQLTypeScript
About the role
Key responsibilities & impact- Deploy, configure, and operationalize agentic AI workflows, AI assistants, and AI-powered automations in ServiceNow and enterprise ecosystems
- Translate customer requirements and business processes into technical architectures, implementation plans, and production-ready AI solutions
- Integrate Agent Packs, AI accelerators, workflow solutions, APIs, enterprise systems, data platforms, and AI services
- Tailor AI solutions to customer operating models, processes, data, security requirements, and user needs
- Support workshops, discovery sessions, technical working sessions, demonstrations, pilots, and production rollouts
- Build enterprise AI applications and workflows using Claude, the Anthropic API, and other LLM platforms
- Implement prompt/context engineering, structured outputs, tool use, API integrations, orchestration, RAG, validation, grounding, and human-in-the-loop patterns
- Build demos, prototypes, proof-of-concepts, reusable implementation patterns, solution templates, prompt libraries, integrations, and deployment assets
- Develop secure integrations and supporting components including scripts, microservices, automation logic, integration services, and lightweight user interfaces
- Apply authentication, authorization, secrets management, access controls, logging, error handling, version control, documentation, scalability, observability, and production-readiness practices
- Develop AI evaluation approaches, test cases, metrics, regression testing, safeguards, governance documentation, and operational support procedures
- Monitor and improve deployed solutions for reliability, performance, latency, model usage, cost efficiency, and user experience
- Contribute to NewRocket Intelligence Platform, Value Realization Dashboard, Data Intelligence Platform, Agent Packs, reusable accelerators, playbooks, and product features
- Present and demo solutions, support pre-sales, provide product feedback, troubleshoot AI workflows and integrations, and collaborate with consulting, product, data, AI/ML, ServiceNow, and AI Center of Excellence teams
- Deploy AI-powered workflows across multiple customer engagements and help move use cases from prototype through governed production deployment
Requirements
What you’ll need- 8+ years of experience in software engineering, systems integration, enterprise platforms, workflow automation, or related technical delivery roles
- Deep understanding of, and experience with banking systems and workflows
- 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, AI-enabled automations, conversational experiences, RAG systems, or agentic workflows
- Experience integrating APIs, enterprise applications, data platforms, or workflow systems in production environments
- Proficiency in JavaScript/TypeScript, Python, or similar programming and scripting languages
- Experience with AWS, Microsoft Azure, or Google Cloud
- Familiarity with prompt engineering, context windows, token usage, embeddings, vector search, RAG, tool use/function calling, structured outputs, and model evaluation
- Understanding of responsible AI concepts, sensitive-data handling, identity and access controls, human oversight, AI safety, and secure AI deployment
- Experience in customer-facing engineering, consulting, technical implementation, solutions architecture, or professional-services roles
- Ability to manage ambiguity, prioritize effectively, travel approximately 25%, and deliver high-quality solutions in fast-moving customer environments
- Preferred: hands-on Anthropic API, Claude models, Anthropic Console, Claude Code, MCP, ServiceNow, vector databases, embeddings, LangChain/LangGraph/LlamaIndex/Semantic Kernel, Docker, CI/CD, SQL, Git, infrastructure-as-code, and secure cloud deployment experience
Benefits
Comp & perks- Diverse and inclusive workplace
- Equal opportunity workplace and affirmative action employer
- Disability accommodations available upon request