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Hourly Ai Policy Jobs (NOW HIRING)

3ds

AI/ML Developer

Long Beach, CA · On-site

$140K - $160K/yr

... policy of non-discrimination and equal opportunity for all employees and qualified applicants ... hourly compensation) and target bonus.

3DS Inc

AI/ML Developer

Long Beach, CA · On-site

$140K - $160K/yr

... policy of non-discrimination and equal opportunity for all employees and qualified applicants ... hourly compensation) and target bonus.

3DS Inc

AI/ML Developer

Long Beach, CA · On-site

$140K - $160K/yr

... policy of non-discrimination and equal opportunity for all employees and qualified applicants ... hourly compensation) and target bonus.

ManTech

Enterprise AI Security Engineer

Washington, DC · Remote

$141K - $236K/yr

You will integrate security and policy enforcement across the AI platform. Responsibilities include ... There are differentiating factors that can impact a final salary/hourly rate, including, but not ...

Meta

AI Research Scientist, Physical AI

New York, NY · On-site

$184K/yr

... policy development, computer vision (3D), egocentric perception, embodied AI and/or LLMs, control ... Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual ...

Fractal Analytics Inc.

$150 - $200/hr

Benefits * As a full‑time employee of the company or an hourly employee working more than 30 ... We also follow a "free time" PTO policy, allowing you the flexibility to take the time needed for ...

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Hourly Ai Policy information

What is the difference between Hourly Ai Policy vs Data Analyst?

AspectHourly Ai PolicyData Analyst
Required CredentialsRelevant certifications in AI, policy, or related fieldsBachelor's or master's in data science, statistics, or related fields
Work EnvironmentPolicy development, AI compliance, remote or office-basedData analysis, reporting, often in office or remote settings
Industry UsageTech companies, AI firms, regulatory agenciesBusiness, finance, healthcare, tech industries
Search & Comparison IntentUnderstanding AI policy roles and responsibilitiesComparing data analysis roles and skills

The comparison between Hourly Ai Policy and Data Analyst highlights that both roles require analytical skills but focus on different areas. Hourly Ai Policy professionals specialize in AI regulations and policy development, often working in tech or regulatory sectors. Data Analysts focus on interpreting data to inform business decisions. While their skills overlap in data handling, their core responsibilities and industry applications differ significantly.

What cities are hiring for Hourly Ai Policy jobs?

Cities with the most Hourly Ai Policy job openings:

What are the most commonly searched types of Ai Policy jobs?

The most popular types of Ai Policy jobs are:

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States with the most job openings for Hourly Ai Policy jobs include:

Hourly Ai Policy jobs near you
Infographic showing various Hourly Ai Policy job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 16% Part Time, and 1% Contract. Highlights an 94% Physical, 2% Hybrid, and 4% Remote job distribution.

Enterprise Architect AI Platform & Generative AI (Mythos Foundation)

Imagine Staffing Technology

Buffalo, NY • Remote

$66.75 - $86.25/hr

Full-time

Re-posted 14 days ago

Job description

Job Title: Enterprise Architect – AI Platform & Generative AI (Mythos Foundation)
Location: Remote (Within USA)
Hire Type: Contract
Pay Range: Competitive Hourly Rate
Work Model: Remote with periodic travel to Buffalo, NY
Schedule: Monday – Friday, Standard Business Hours
Recruiter Contact: Samantha Marranca | 716-256-1271 | smarranca@imaginestaffing.net
 
NO C2C, NO sponsorship given at this time
 
Nature & Scope:
Positional Overview
Our client is seeking an experienced Enterprise Architect to lead the strategic architecture and evolution of its enterprise AI platform, known as Mythos. This role will define the future-state architecture, governance frameworks, standards, and reusable design patterns that enable scalable, secure, and responsible adoption of artificial intelligence across the organization.
The Enterprise Architect will serve as the architectural leader for enterprise AI initiatives, partnering closely with security, risk, data, infrastructure, platform engineering, and business stakeholders to establish a comprehensive AI platform strategy. This individual will be responsible for defining conceptual and logical architectures, developing enterprise roadmaps, and ensuring AI capabilities are aligned with business objectives, regulatory requirements, and operational needs.
This position is ideal for a senior architecture professional with deep experience in enterprise architecture, AI platforms, cloud technologies, governance frameworks, and emerging technology strategy.
 
Role & Responsibility:
Tasks That Will Lead To Your Success
Enterprise Architecture Leadership
  • Define and maintain the enterprise architecture vision, roadmap, and target-state design for the Mythos AI platform. 
  • Develop conceptual, logical, and high-level physical architecture patterns for enterprise AI adoption. 
  • Establish enterprise standards, governance models, and reusable architecture frameworks supporting AI capabilities. 
  • Collaborate with executive leadership and technology stakeholders to align AI strategy with business priorities. 
  • Communicate architecture vision, technology tradeoffs, and strategic recommendations to senior leadership. 
  • Participate in enterprise architecture governance and strategic planning initiatives.
AI Platform Strategy & Governance
  • Define architecture standards for model access, model lifecycle management, telemetry, observability, and AI governance. 
  • Establish enterprise guardrail frameworks supporting responsible AI adoption. 
  • Develop architectural controls addressing security, compliance, privacy, risk, and ethical AI considerations. 
  • Create decision frameworks supporting model selection and deployment strategies. 
  • Define fit-for-purpose guidelines balancing cost, performance, risk, latency, and business value. 
  • Drive the evolution of enterprise AI platform capabilities and adoption patterns.
Architecture Planning & Innovation
  • Research emerging technologies, AI platforms, and industry trends to identify opportunities for enterprise adoption. 
  • Develop architecture roadmaps that support long-term scalability and innovation. 
  • Partner with business and technology leaders to evaluate new platform capabilities and strategic initiatives. 
  • Promote reuse of enterprise services, platforms, and architecture patterns. 
  • Provide architectural guidance supporting future AI-enabled business solutions.
AI Telemetry & Observability
  • Define enterprise observability standards for AI systems and platforms. 
  • Establish architecture patterns supporting visibility into model behavior, usage, performance, and risk indicators. 
  • Develop governance frameworks for monitoring model activity and enforcing usage policies. 
  • Support architecture strategies for preventing misuse, bias, data leakage, and regulatory exposure.
Cross-Functional Leadership
  • Partner with security, risk, compliance, data, platform engineering, and application development teams. 
  • Provide architecture consultation and technical leadership across multiple initiatives. 
  • Support solution architects and engineering teams through architecture reviews and governance activities. 
  • Ensure architectural consistency across AI, cloud, infrastructure, and business application domains.
 
Skills & Experience
Qualifications That Will Help You Thrive
Required Experience
  • Bachelor’s Degree in Computer Science, Information Technology, Engineering, or related discipline. 
  • 7+ years of experience in Enterprise Architecture, Solution Architecture, or Technology Strategy. 
  • Experience developing enterprise architecture roadmaps and target-state architectures. 
  • Strong understanding of AI platforms, cloud technologies, and enterprise software architecture. 
  • Experience establishing governance, standards, and architecture frameworks. 
  • Knowledge of software engineering, application integration, and cloud-native architectures. 
  • Ability to communicate effectively with executive leadership and technical teams. 
  • Strong analytical, strategic planning, and decision-making skills.
Preferred Qualifications
  • Graduate degree in a technical or business discipline. 
  • Experience supporting Generative AI, LLM, or AI platform initiatives. 
  • Cloud certifications within Azure, AWS, or Google Cloud. 
  • Enterprise Architecture certifications (TOGAF or equivalent). 
  • Experience working within highly regulated industries. 
  • Financial services experience preferred. 
  • Familiarity with AI governance, responsible AI, and model risk frameworks.
 
Team & Environment
  • Partners with executive leadership, enterprise architecture, security, risk, and engineering teams.