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Contract Ai Implementation Jobs in Arizona (NOW HIRING)

BTree Solutions, Inc.

AI MANAGER

Vail, AZ · On-site

USC, GC, H1B and EAD Contract Type: W2 This position manages a team of five AI professionals ... implementation. Job Duties: AI Tool Development & Application Delivery: * Leads the design ...

Versaterm

Implementation Specialist

Mesa, AZ · On-site

AI is central to where we're going. Not as a feature but as core infrastructure. We're embedding ... Please note that specific customer contracts may impose additional security verification ...

Versaterm

Implementation Specialist

Mesa, AZ

Experience using AI tools as part of daily support workflows to enhance productivity, improve ... Please note that specific customer contracts may impose additional security verification ...

Versaterm

Project Implementation Lead

Mesa, AZ · On-site

AI is central to where we're going. Not as a feature but as core infrastructure. We're embedding ... Please note that specific customer contracts may impose additional security verification ...

Acron Aviation

Principal, Contracts Manager

Phoenix, AZ

$88K - $118K/yr

Ability to use approved AI-enabled tools responsibly to support contract review, drafting, research ... Process-improvement mindset with the ability to identify inefficiencies and help implement scalable ...

Staffingine LLC

AI Engineer

Phoenix, AZ · On-site

Contract * Develop and implement AI solutions using Python and AI frameworks such as Langgraph and Langchain Work with vector databases like Pinecone to manage and query highdimensional data Build ...

Lorven Technologies

AI Engineering Leader

Tempe, AZ · On-site

$98K - $129K/yr

... Months Contract Role Overview We are seeking a highly hands-on AI Engineering leader with deep ... Multi-agent architectures Retrieval-Augmented Generation (RAG) pipelines GraphRAG implementations ...

Lorven Technologies

AI Solution Architect

Tempe, AZ · On-site

$60.25 - $79.50/hr

Austin, Tx | Tempe, Az | Charlotte, NC | New York, NY - Onsite Duration: 12 Months Contract Role ... This role is central to shaping and implementing an AI-first Product Delivery Lifecycle (PDLC ...

Trinite Consulting Group LLC

AI/ML Engineer

Phoenix, AZ · On-site

$55/hr

Scottsdale, AZ or Dallas, TX (HYBRID) Duration: Long Term Contract Rate: $55/hr C2C Note: Must ... This role involves developing MCP servers and agents, integrating LLMs, and implementing RAG ...

World View

Contracts Manager

Tucson, AZ · On-site +1

$120K - $130K/yr

By combining multi-domain platforms, advanced sensing, secure networks, and AI-enabled analytics ... Manage contract changes, modifications, claims, and dispute resolution. * Provide guidance to ...

World View

Contracts Manager

Tucson, AZ · On-site +1

$120K - $130K/yr

By combining multi-domain platforms, advanced sensing, secure networks, and AI-enabled analytics ... Manage contract changes, modifications, claims, and dispute resolution. * Provide guidance to ...

Conch Technologies Inc

Avaya Engineer ( AI/ML )

Phoenix, AZ · On-site

$96K - $132K/yr

Phoenix, AZ, Charlotte, NC, and Sunrise, FL ( Onsite 5 days a week ) Duration: 12+ Months Contract ... Implement NLP, AI/ML, and conversational AI capabilities * Integrate Five9 and Google CCAI/IVA ...

Conch Technologies Inc

AI/ML NLP Engineer

Phoenix, AZ · On-site

Phoenix, AZ, Charlotte, NC, and Sunrise, FL ( Onsite 5 days a week ) Duration: 12+ Months Contract ... Implement NLP, AI/ML, and conversational AI capabilities * Integrate Five9 and Google CCAI/IVA ...

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All JobsContract Ai Implementation JobsContract Ai Implementation Jobs in Arizona

Contract Ai Implementation information

What is the difference between Contract Ai Implementation vs Data Scientist?

AspectContract Ai ImplementationData Scientist
Required CredentialsTypically requires AI/ML certifications, programming skills, and project management experienceRequires degrees in data science, statistics, or related fields, often with advanced degrees
Work EnvironmentProject-based, client-focused, often freelance or consulting rolesFull-time or research roles within organizations or academia
Industry UsageUsed across various industries for specific AI projectsApplied in data analysis, research, and model development within organizations

Contract Ai Implementation professionals focus on delivering AI solutions on a project basis, often working with clients and requiring specific certifications. Data Scientists typically work within organizations, conducting research and developing models, often with advanced degrees. Both roles overlap in technical skills but differ in work setting and scope.

What is a contract AI implementation specialist?

A Contract AI Implementation specialist is a professional who helps organizations integrate artificial intelligence solutions into their contract management processes. This role involves assessing business needs, selecting appropriate AI technologies, and overseeing the deployment of tools that automate tasks like contract analysis, risk assessment, and compliance monitoring. The specialist ensures that the AI system aligns with legal standards and company policies while streamlining workflows and improving efficiency. They often collaborate with legal, IT, and procurement teams to ensure a smooth transition and optimal use of AI in managing contracts.

What are the key skills and qualifications needed to thrive as a contract AI implementation specialist?

To thrive as a Contract AI Implementation Specialist, you need expertise in AI concepts, contract management, and a relevant technical or business degree, often with experience in legal tech or AI deployment. Familiarity with tools such as contract lifecycle management (CLM) platforms, machine learning frameworks, and data integration systems is typically required. Strong problem-solving, communication, and project management skills help you collaborate across legal, IT, and business teams. These skills ensure successful AI-driven contract solutions that streamline workflows, minimize risk, and deliver business value.

What are some common challenges faced by professionals in contract AI implementation roles, and how can they be addressed?

Professionals working in Contract AI Implementation often encounter challenges such as integrating AI solutions with existing contract management systems, ensuring data privacy and security, and managing change within the organization. To address these, it's important to work closely with IT and legal teams, prioritize stakeholder communication, and provide comprehensive training to end-users. Staying up to date with evolving AI technologies and regulatory requirements also helps in proactively identifying and mitigating risks during implementation.
What are the most commonly searched types of Ai Implementation jobs in Arizona? The most popular types of Ai Implementation jobs in Arizona are:
What are popular job titles related to Contract Ai Implementation jobs in Arizona? For Contract Ai Implementation jobs in Arizona, the most frequently searched job titles are:
What job categories do people searching Contract Ai Implementation jobs in Arizona look for? The top searched job categories for Contract Ai Implementation jobs in Arizona are:
What cities in Arizona are hiring for Contract Ai Implementation jobs? Cities in Arizona with the most Contract Ai Implementation job openings:
Contract Ai Implementation jobs near you
Infographic showing various Contract Ai Implementation job openings in Arizona as of August 2026, with employment types broken down into 66% Full Time, 7% Part Time, 6% Temporary, and 21% Contract. Highlights an 71% In-person, and 29% Remote job distribution.

AI MANAGER

BTree Solutions, Inc.

Vail, AZ • On-site

Contractor

Re-posted 16 days ago

Job description

Job Title: AI MANAGER
Location: Tucson, AZ
Duration: 12+ Months
Visa: USC, GC, H1B and EAD
Contract Type: W2
This position manages a team of five AI professionals responsible for designing, developing, and deploying AI-powered tools, applications, and capabilities that advance the University's academic, research, and administrative priorities. The manager drives applied AI strategy, identifies high-impact opportunities for AI tool adoption across campus, and ensures delivered solutions are scalable, responsible, and aligned with institutional AI governance standards. The position serves as a key bridge between emerging AI technologies and the practical needs of faculty, staff, students, and campus partners, championing innovation while maintaining rigorous standards for responsible AI implementation.
Job Duties:
AI Tool Development & Application Delivery:
  • Leads the design, development, and deployment of AI-powered tools, applications, and workflows for campus use, with a focus on practical, high-impact solutions that advance University research, teaching, and operational objectives.
  • Manages the full application development lifecycle from requirements gathering and prototyping through testing, deployment, and iteration.
  • Ensures developed tools meet institutional standards for responsible AI, data privacy, accessibility, and security.
  • Directs team members in applying AI/ML techniques, LLM integrations, API development, and software engineering best practices to deliver reliable, scalable campus solutions

Team Leadership & Professional Development:
  • Plans, directs, and evaluates the day-to-day work of a team of five AI professionals, including AI/ML engineers, developers, and applied researchers.
  • Establishes clear performance expectations, provides ongoing coaching and feedback, and conducts formal performance evaluations.
  • Identifies and supports individual development opportunities to build technical depth and innovation capacity across the team.
  • Fosters a collaborative, mission-driven team environment aligned with ORAI's responsible AI values and the University's commitment to inclusive excellence.

Campus AI Innovation & Stakeholder Engagement:
  • Identifies, prioritizes, and advances opportunities to deploy AI tools and capabilities that meet the evolving needs of campus faculty, staff, students, and administrative units.
  • Partners with colleges, departments, and research groups to understand requirements and co-develop applied AI solutions.
  • Communicates AI tool capabilities, limitations, and responsible use guidelines to various campus audiences.
  • Represents AI²S/ORAI in campus working groups, advisory bodies, and innovation initiatives related to applied AI adoption.
  • Research Software Engineering & Technical Infrastructure:
  • Applies research software engineering principles to ensure AI tools and applications are built on robust, maintainable, and interoperable technical foundations.
  • Oversees integration of AI capabilities with existing University platforms, APIs, and research computing infrastructure, including cloud-based AI services (e.g., AWS Bedrock).
  • Ensures documentation, version control, testing protocols, and deployment pipelines meet institutional and software engineering standards.
  • Collaborates with the Cyberinfrastructure & Systems team to align application development with underlying infrastructure capabilities.

AI Governance, Responsible AI Compliance & Reporting:
  • Ensures all AI tools and applications developed by the team adhere to the University's responsible AI framework, data governance policies, and applicable regulatory requirements.
  • Reviews and evaluates AI solutions for bias, fairness, transparency, and alignment with ethical AI principles.
  • Contributes to ORAI AI governance activities, policy development, and institutional reporting on applied AI initiatives.
  • Maintains awareness of emerging AI technologies, regulatory developments, and peer institution practices to inform continuous improvement of the team's approach.

Knowledge, Skills and Abilities:
  • Practical knowledge of AI/ML concepts, techniques, and application development, including large language models (LLMs), generative AI, predictive modeling, and data analysis.
  • Knowledge and understanding of research software engineering principles, software development lifecycles, and technical documentation standards.
  • Knowledge of responsible AI frameworks, data privacy regulations (e.g., FERPA, HIPAA applicability), and institutional AI governance practices.
  • Knowledge and understanding of cloud AI platforms, API ecosystems, and integration patterns for enterprise AI tool deployment.
  • Knowledge and understanding of responsible AI principles, data privacy regulations, and AI governance frameworks.
  • Strong applied AI and software development skills, with demonstrated ability to move from concept to working application.
  • Effective team leadership and people management skills, including performance coaching, goal-setting, and staff development.
  • Ability to provide clear and accessible communication skills, including the ability to explain AI capabilities and limitations to non-technical campus stakeholders.
  • Project management and prioritization skills, with the ability to manage multiple concurrent initiatives in a dynamic environment.
  • Proficiency in AI/ML frameworks and tools (e.g., Python, LangChain, OpenAI/Anthropic APIs, Hugging Face, or equivalent) and software development practices including version control, CI/CD, and API development.
  • Ability to identify high-impact opportunities for AI tool adoption and translate campus needs into practical, responsible AI solutions.
  • Ability to build collaborative relationships across varioius university stakeholders, including faculty, staff, administrators, and technical teams.
  • Ability to stay current with rapidly evolving AI technologies and evaluate their applicability and responsible use in a university context.
  • Ability to cultivate an innovative, and mission-aligned team culture consistent with ORAI's responsible AI values.

Preferred Qualifications:
  • Experience designing, developing, and deploying AI/ML-powered tools or applications in an applied or enterprise environment.
  • Experience managing or leading a technical team, including setting priorities, evaluating performance, and supporting professional development.
  • Experience working with cloud-based AI platforms (e.g., AWS Bedrock, Azure OpenAI, or equivalent) preferred.
  • Experience in a higher education, research, or public sector environment preferred.
  • Master's degree in Computer Science, Artificial Intelligence, Data Science, Information Science, or a related field preferred

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