Application Architect

Data And Knowledge Engineer - AiGenesis10 is currently seeking a Data and Knowledge Engineer - AI for a hybrid position (3 days onsite per week) with a Global Financial Institution located in Chandler, AZ. This is a 12+ month contract opportunity.This role is responsible for leading the design, governance, and continuous improvement of the data and knowledge foundations that support AI and agentic capabilities across Network Services. The ideal candidate will work across both structured and unstructured data sources to ensure information is defined, organized, governed, and made available in a manner suitable for trusted AI consumption. This individual partners closely with product and service subject matter experts to understand network technologies, operational workflows, and domain context so that high-quality data and knowledge can be translated into reusable AI-ready assets.Responsibilities:Lead the design and improvement of data and knowledge assets that support AI and agentic use-cases across Network Services, including both structured and unstructured sourcesDefine and maintain standards for how documentation, configurations, telemetry, metadata, policies, standards, and operational knowledge should be organized, governed, and prepared for AI consumptionPartner with product and service subject matter experts to understand network technologies, operational context, and domain-specific knowledge required to improve model grounding and decision qualityDesign and guide scalable methods for storing, governing, indexing, validating, and retrieving context assets needed for AI-enabled workflows and solutionsEstablish and evolve preventative and detective controls that identify and reduce data quality, metadata quality, knowledge quality, lineage, and freshness issues before they affect downstream AI useLead remediation efforts for material data and knowledge quality issues by identifying upstream root causes, defining corrective actions, and improving reliability of source processes and assetsDefine expectations for ownership, stewardship, lineage, freshness, governance, and control accountability across relevant data and knowledge domainsBuild or guide the development of pipelines, transformations, validation routines, metadata structures, and supporting services that improve the quality and accessibility of AI-relevant context assetsCreate and improve reusable templates, patterns, and guidance for documentation, knowledge artifacts, metadata practices, and context management standardsWork across engineering, architecture, operations, and governance teams to ensure data and knowledge practices align with enterprise controls, delivery needs, and approved standardsMonitor and communicate the health, readiness, and quality of AI-relevant data and knowledge assets, including control gaps, remediation priorities, and material risks to trusted model consumptionMentor less senior engineers and contributors on data engineering, knowledge engineering, control design, and context management practicesContribute to continuous improvement of data and knowledge management practices that strengthen trust, reuse, traceability, and operational supportability of AI context across the organizationDocument standards, definitions, controls, transformations, and usage considerations so that downstream teams can reliably consume, govern, and support resulting data and knowledge assetsRequirements:Strong experience engineering and governing both structured and unstructured data used for analytics, automation, search, or AI-enabled solutionsAdvanced understanding of data modeling, transformation, storage, indexing, retrieval, and metadata management patternsDemonstrated ability to define enterprise-ready standards for how data, documents, knowledge artifacts, metadata, and operational context should be structured and prepared for AI consumptionExperience establishing and improving data quality, metadata quality, and knowledge quality controlsStrong knowledge of preventative and detective controls used to identify, prevent, and remediate issues related to data and knowledge management practicesExperience working with knowledge sources such as policies, standards, configurations, telemetry, runbooks, architecture artifacts, and operational documentationAbility to work closely with subject matter experts to interpret operational knowledge and translate it into reusable, governed data and knowledge assetsStrong working understanding of network technologies, infrastructure concepts, and service modelsExperience defining data ownership, stewardship, lineage, freshness, governance, and usage expectations in a regulated enterprise environmentFamiliarity with AI-oriented data and knowledge preparation concepts, including grounding, retrieval-readiness, context structuring, and metadata enrichmentAbility to design scalable approaches for storing, governing, indexing, validating, and retrieving contextual assetsStrong analytical and problem-solving skills, including the ability to identify upstream causes of context quality issuesExperience leading or influencing cross-functional work across engineering, architecture, operations, and governance stakeholdersStrong written and verbal communication skills with the ability to document standards, controls, and definitions for technical and non-technical audiencesExperience working in a fast-paced and complex environment with evolving prioritiesPay range: $60.24 - $68.24 per hourOnly candidates available and ready to work directly as Genesis10 employees will be considered for this position.If you have the described qualifications and are interested in this exciting opportunity, please apply!