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Executive Graphql Jobs in Virginia (NOW HIRING)

Jobtailor

Lead Agentic AI Engineer

Mclean, VA · On-site

$140 - $210/hr

Experience working with enterprise API ecosystems REST, GraphQL, or pub/sub architectures at ... executives depend on * Comfortably operating in distributed, multi-program environments with ...

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Executive Graphql information

What is the difference between Executive Graphql vs Data Engineer?

AspectExecutive GraphqlData Engineer
Required CredentialsExperience with GraphQL, API management, leadership skillsComputer science degree, SQL, Python, ETL tools
Work EnvironmentTech teams, product development, leadership rolesData pipelines, backend systems, cloud platforms
Employer & Industry UsageTech companies, startups, SaaS providersData-driven companies, finance, tech, healthcare
Search & Comparison IntentUnderstanding leadership roles in API/GraphQLData infrastructure and pipeline roles

The Executive Graphql role focuses on leading API strategies and managing GraphQL implementations within tech teams, often requiring leadership experience and API expertise. Data Engineers build and maintain data pipelines, requiring technical skills in data processing and database management. While both roles operate in tech environments, they serve different functions—one in API management and leadership, the other in data infrastructure development.

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The most popular types of Graphql jobs in Virginia are:

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Executive Graphql jobs near you

Lead Agentic AI Engineer

Jobtailor

Mclean, VA • On-site

$140 - $210/hr

Other

Posted 7 days ago

Job description

Responsibilities
  • Own the desk's delivery. Be accountable for the full output of the Mission Support Desk across all programs it serves response quality, turnaround time, and the accuracy of AI-generated outputs.
  • Design and operate agentic AI workflows. Build, refine, and maintain the agentic pipelines that support desk operations including triage, data retrieval, summarization, reporting, and escalation routing.
  • Own the configuration, prompt architecture, and reliability of every workflow in production.
  • Integrate across Orbis products. Work with Catalyst, Pulse, and Discovery to ensure the support desk can access and act on data flowing through the governed data fabric surfacing the right information at the right time, in the right format, for the right consumer.
  • Set the quality bar. Define what "good" looks like for AI-assisted support output accuracy standards, human review checkpoints, escalation criteria, and documentation requirements.
  • Hold the team and the systems to it.
  • Manage and develop the team. Lead a team of support specialists. Identify skill gaps, give direct performance feedback, and build pathways for growth as AI tooling evolves. The people you develop are the capability you leave behind.
  • Build and maintain playbooks. Author and continuously improve the standard operating procedures, prompt templates, agent configurations, and escalation runbooks that govern how the desk operates. Nothing should live only in someone's head.
  • Track and report performance. Own the metrics that matter resolution rate, escalation rate, AI output accuracy, response time, and program satisfaction. Report clearly to program leadership and internal stakeholders, with proposed actions, not just status.
  • Identify and close capability gaps. Recognize when a support need is not served by existing AI tooling, scope the gap clearly, and work with engineering or product teams to close it. Surface problems early with proposed mitigations.
  • Coordinate across programs. Serve as the operational point of contact for program teams consuming support desk services. Translate their requirements into workflow updates and configuration changes without disrupting active operations.
  • Stay current. Track developments in agentic AI tooling, LLM capabilities, and enterprise AI platforms. Assess what is worth adopting, at what pace, and for which programs and make those calls with confidence.
Requirements
  • 5+ years of professional experience in operations, technical program management, managed services, or AI/data roles
  • Demonstrated experience designing and operating workflows powered by LLM-based agents or agentic AI frameworks (e.g., Claude, GPT-4, LangChain, AutoGen, or equivalents)
  • Proven ability to manage a team and be accountable for its collective output, not just individual contributions
  • Strong working knowledge of prompt engineering, retrieval-augmented generation (RAG), and AI agent orchestration patterns
  • Experience working with enterprise API ecosystems REST, GraphQL, or pub/sub architectures at production scale
  • Ability to assess and communicate the reliability and limitations of AI outputs with precision; knows when to trust the model and when not to
  • Excellent written communication this role produces documentation, SOPs, and performance reports that program leads and executives depend on
  • Comfortably operating in distributed, multi-program environments with competing priorities and shifting program needs.
Hard Skills
  • AI workflows
  • agentic AI
  • prompt engineering
  • retrieval-augmented generation
  • AI agent orchestration
  • API ecosystems
  • REST
  • GraphQL
  • LLM-based agents
  • workflow design
Soft Skills
  • team management
  • accountability
  • communication
  • performance feedback
  • problem-solving
  • adaptability
  • leadership
  • documentation
  • collaboration
  • organizational skills
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