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Director Ai Data Entry Jobs (NOW HIRING)

Our state-of-the-art data technologies, lean AI agile methodologies, and cohesive teams of the ... Directing the build of robust agent harnesses - orchestration layers, evaluation frameworks ...

Join us to put AI to work for people. The Global Director of Data and Analytics GTM at ServiceNow will spearhead the development and execution of the go-to-market strategy for data and analytics ...

Join us to put AI to work for people. The Global Director of Data and Analytics GTM at ServiceNow will spearhead the development and execution of the go-to-market strategy for data and analytics ...

Join us to put AI to work for people. The Global Director of Data and Analytics GTM at ServiceNow will spearhead the development and execution of the go-to-market strategy for data and analytics ...

Join us to put AI to work for people. The Global Director of Data and Analytics GTM at ServiceNow will spearhead the development and execution of the go-to-market strategy for data and analytics ...

KPMG is currently seeking a Director of AI, Data & Google Cloud to join our consulting organization. Responsibilities: * Lead end-to-end AI, data, and cloud transformation programs using Google Cloud ...

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KPMG is currently seeking a Director of AI, Data & Google Cloud to join our consulting organization. Responsibilities: * Lead end-to-end AI, data, and cloud transformation programs using Google Cloud ...

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KPMG is currently seeking a Director of AI, Data & Google Cloud to join our consulting organization. Responsibilities: * Lead end-to-end AI, data, and cloud transformation programs using Google Cloud ...

New

KPMG is currently seeking a Director of AI, Data & Google Cloud to join our consulting organization. Responsibilities: * Lead end-to-end AI, data, and cloud transformation programs using Google Cloud ...

New

KPMG is currently seeking a Director of AI, Data & Google Cloud to join our consulting organization. Responsibilities: * Lead end-to-end AI, data, and cloud transformation programs using Google Cloud ...

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Director Ai Data Entry information

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$52K

$128.5K

$200K

How much do director ai data entry jobs pay per year?

As of Sep 5, 2026, the average yearly pay for director ai data entry in the United States is $128,526.00, according to ZipRecruiter salary data. Most workers in this role earn between $94,000.00 and $163,500.00 per year, depending on experience, location, and employer.

What is a director AI data entry?

Director AI Data Entry jobs involve overseeing teams and processes related to managing, verifying, and optimizing data entry for artificial intelligence projects. This role typically includes developing strategies for efficient data collection, ensuring data accuracy, and implementing best practices for training AI models. Directors in this field work closely with data scientists, engineers, and entry staff to ensure high-quality datasets, compliance with privacy standards, and the smooth operation of large-scale AI data pipelines. The position requires strong leadership skills, technical expertise in data management, and a deep understanding of AI data requirements.

What are the key skills and qualifications needed to thrive as a director AI data entry?

To thrive as a Director of AI Data Entry, you need expertise in data management, AI/machine learning fundamentals, and a relevant degree such as computer science or information systems. Familiarity with data annotation tools, project management software, and AI platforms like TensorFlow or PyTorch is typically required, along with certifications in data science or project management. Strong leadership, attention to detail, and effective communication are critical soft skills for coordinating teams and ensuring data quality. These skills ensure efficient workflow, high-quality datasets, and successful integration of AI solutions within organizational goals.

How does a director AI data entry typically collaborate with technical and non-technical teams?

A Director of AI Data Entry frequently bridges the gap between data entry staff, data scientists, and IT professionals to ensure data quality and integrity for AI projects. This role often involves translating project requirements into clear, actionable processes for data entry teams while also communicating data challenges and opportunities to upper management and technical teams. Effective collaboration and clear communication across departments are key, as the director must facilitate workflow alignment, resolve data issues, and support seamless integration of AI data pipelines. Regular meetings and status updates are common, and the director is expected to foster a culture of accuracy and continuous improvement.

What cities are hiring for Director Ai Data Entry jobs?

Cities with the most Director Ai Data Entry job openings:

What are the most commonly searched types of Ai Data Entry jobs?

The most popular types of Ai Data Entry jobs are:

What states have the most Director Ai Data Entry jobs?

States with the most job openings for Director Ai Data Entry jobs include:

Infographic showing various Director Ai Data Entry job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution, with an average salary of $128,526 per year, or $61.8 per hour.

Sr. Director, AI, Data & Architecture

Omnicell

Fort Worth, TX • On-site

$180 - $280/hr

Other

Re-posted 19 days ago


Key responsibilities

  • Lead and define EnlivenHealth's AI strategy, including identifying and guiding AI use cases to improve product capabilities and customer outcomes.

  • Establish and oversee data platform strategy, including data architecture, governance, quality, and enabling analytics and AI readiness.

  • Define and maintain enterprise and solution architecture standards, lead solution architecture for major initiatives, and drive technical modernization efforts.


Omnicell rating

7.8

Company rating: 7.8 out of 10

Based on 24 frontline employees who took The Breakroom Quiz

130th of 247 rated software companies


Job description

Senior Director, AI, Data, and Architecture Position Summary

The Senior Director, AI, Data, and Architecture is responsible for leading EnlivenHealth’s AI strategy, data platform direction, enterprise architecture, and technical modernization across the Product and Engineering organization.

This role serves as a senior technical leader responsible for helping EnlivenHealth responsibly apply AI to improve product capabilities, engineering productivity, analytics, automation, and customer outcomes. The Director will define practical AI patterns, data foundations, architecture standards, and modernization roadmaps that enable scalable, secure, reliable, and innovative healthcare technology solutions.

The Senior Director partners closely with Product, Engineering, Platform, Security, Cloud Operations, Quality, and business stakeholders to translate business priorities into executable AI, data, integration, and architecture plans. This role requires strong technical judgment, healthcare technology experience, and the ability to influence across teams without relying solely on direct authority.

Key Responsibilities AI Strategy and Enablement
  • Define and lead EnlivenHealth’s AI strategy across Product and Engineering.
  • Identify, prioritize, and guide AI use cases that improve patient engagement, clinical workflows, financial operations, analytics, automation, and internal productivity.
  • Establish AI architecture patterns, development standards, lifecycle practices, evaluation methods, and guardrails for responsible AI adoption.
  • Partner with Product leaders to develop customer-facing AI capabilities that create measurable value while respecting healthcare privacy, security, explainability, and customer trust requirements.
  • Partner with Engineering and Quality teams to expand AI-assisted software development, test automation, documentation, code review, knowledge management, and operational workflows.
  • Track AI adoption, productivity impact, quality impact, risks, and lessons learned.
  • Ensure AI initiatives align with Omnicell and EnlivenHealth policies, customer commitments, data-use obligations, and applicable regulatory expectations.
Data Platform Strategy and Governance
  • Define the strategic direction for EnlivenHealth’s data platform, including data architecture, data flows, data quality, data governance, analytics enablement, and AI readiness.
  • Support the development of a broader patient, pharmacy, financial, clinical, and outcomes data foundation.
  • Establish practical standards for data ingestion, transformation, storage, lineage, access, quality, retention, and security.
  • Partner with Security, Privacy, Legal, Compliance, Product, and Engineering stakeholders to ensure healthcare data is handled appropriately.
  • Identify opportunities to consolidate data assets, reduce duplication, and create trusted data products.
Enterprise and Solution Architecture
  • Define and maintain enterprise architecture principles, standards, decision practices, and reference patterns for EnlivenHealth platforms.
  • Lead solution architecture for major product initiatives, platform modernization, integrations, AI-enabled capabilities, and data-driven services.
  • Partner with Product and Engineering leaders to ensure architecture decisions align with customer needs, scalability, security, reliability, interoperability, and operating efficiency.
  • Identify technical debt, architectural risk, platform fragmentation, and scalability constraints; develop practical plans to address them.
Modernization, API, and Integration Architecture
  • Own and maintain the technical modernization roadmap in partnership with Product, Engineering, Platform, Security, and Cloud Operations.
  • Drive patterns that simplify platforms, reduce operational risk, improve resiliency, and enable faster product delivery.
  • Define API and integration architecture standards, including authentication, authorization, versioning, monitoring, documentation, and lifecycle management.
  • Support scalable integration with pharmacy management systems, health systems, payers, partners, and other healthcare ecosystem participants.
Required Qualifications & Skills
  • 10+ years of progressive experience in software engineering, enterprise architecture, solution architecture, data architecture, cloud architecture, AI enablement, or related technology leadership roles.
  • 5+ years leading architecture, technical strategy, data platform, AI, or modernization initiatives across complex SaaS or enterprise software environments.
  • Practical experience with AI technologies and implementation patterns, including generative AI, machine learning concepts, responsible AI practices, model evaluation, prompt/workflow design, and AI-enabled software delivery.
  • Experience defining AI standards, architecture roadmaps, technical patterns, integration approaches, and modernization strategies.
  • Strong understanding of cloud-native architecture, distributed systems, APIs, data platforms, security patterns, observability, resiliency, and scalable SaaS operations.
  • Experience with data architecture, data governance, analytics enablement, and modern data platform concepts.
  • Strong knowledge of healthcare data privacy, security, compliance, and customer trust considerations, including HIPAA, SOC 2, HITRUST, or similar control environments.
  • Excellent communication skills with the ability to explain complex technical tradeoffs to technical, executive, customer, and non-technical audiences.
  • Proven ability to balance innovation, execution, security, operational reliability, and long-term platform health.
Preferred Qualifications
  • Bachelor’s degree in Computer Science, Engineering, Information Systems, Data Science, or related field.
  • Master’s degree or MBA with a technology, data, AI, or healthcare focus.
  • Experience in healthcare technology, pharmacy technology, patient engagement, clinical workflow, claims, or financial technology.
  • Experience with AWS cloud services, AI platforms, event-driven architecture, containerized platforms, serverless technologies, and cloud-native modernization.
  • Experience with AI platforms and services such as AWS Bedrock, Kiro, OpenAI, Anthropic Claude, GitHub Copilot, or comparable technologies.
  • Experience establishing AI governance, responsible AI review processes, model evaluation practices, and secure AI development patterns.
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