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Patterned Learning Ai Jobs in Pennsylvania (NOW HIRING)

hajoca

AI Enablement Lead

Lafayette Hill, PA

Document repeatable patterns, standards, and playbooks that improve the consistency and scalability ... Partner with the Learning Center team and Marketing & Communications to develop and distribute ...

Computer Enterprises, Inc.

AI Solutions Architect

Crafton, PA · On-site

$59.75 - $78.75/hr

... learning pipelines, aligned to client business objectives. * Lead technical strategy for AI ... Mentor technical teams on AI architecture patterns and responsible AI practices. What you will ...

CEI

AI Solutions Architect

Pittsburgh, PA · Remote

$61.25 - $80.50/hr

... learning pipelines, aligned to client business objectives. * Lead technical strategy for AI ... Mentor technical teams on AI architecture patterns and responsible AI practices. What you will ...

Vector8 Group

Technical Lead, Data & AI, CH

Indiana, PA · On-site

$120 - $160/hr

Identify modernization paths and integration patterns that respect operational realities and ... Supportive team culture that prioritises continuous learning, professional development, and ...

Arcfield

Senior Principal Digital Engineer

Monroeville, PA · On-site

$124K - $171K/yr

... Learning (AI/ML) methodologies, and modernizing engineering and operational processes across a ... Knowledge of MBSE patterns, anti-patterns, and best practices for complex systems * Experience with ...

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Patterned Learning Ai information

What are some typical challenges faced by patterned learning AI professionals in implementing AI-driven solutions within organizations?

Patterned Learning AI professionals often encounter challenges such as integrating AI models with existing legacy systems, ensuring high-quality and representative training data, and aligning AI solutions with specific business objectives. Collaboration across multidisciplinary teams—including data scientists, software engineers, and business stakeholders—is essential for successful deployment. Additionally, professionals must stay updated on evolving AI technologies and best practices to maintain model accuracy and address ethical considerations.

What are the key skills and qualifications needed to thrive as a machine learning engineer, and why are they important?

To thrive as a Machine Learning Engineer, you need a strong background in mathematics, statistics, programming (especially Python), and a degree in computer science or a related field. Experience with machine learning frameworks such as TensorFlow, PyTorch, and scikit-learn, as well as familiarity with cloud computing platforms and data management tools, is essential. Excellent problem-solving skills, creativity, and clear communication are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies are vital for developing reliable AI systems that solve real-world problems and drive innovation.

What is the difference between Patterned Learning Ai vs Data Scientist?

AspectPatterned Learning AiData Scientist
Required CredentialsTypically requires machine learning, AI, or computer science degrees; certifications in AI toolsRequires degrees in statistics, computer science, or related fields; often certifications in data analysis
Work EnvironmentTech companies, AI startups, research labs focusing on AI developmentBusiness, finance, healthcare, and tech sectors analyzing data for insights
Employer & Industry UsageUsed by AI-focused organizations developing intelligent systemsEmployed across industries for data analysis, predictive modeling, and decision support

Patterned Learning Ai primarily focuses on developing AI models and algorithms, often requiring specialized technical skills. Data Scientists analyze data to extract insights and inform business decisions. While both roles involve data and machine learning, Patterned Learning Ai is more centered on creating AI systems, whereas Data Scientists interpret data for strategic purposes.

What is patterned learning AI?

Patterned Learning AI refers to artificial intelligence systems designed to recognize, learn from, and replicate patterns in data. These systems use algorithms to identify trends, correlations, and structures within large datasets, enabling them to make predictions or automate decision-making processes. Patterned Learning AI is commonly used in fields like image recognition, natural language processing, and predictive analytics. Its applications help businesses and researchers uncover hidden insights, streamline operations, and improve accuracy in various tasks.
What are popular job titles related to Patterned Learning Ai jobs in Pennsylvania? For Patterned Learning Ai jobs in Pennsylvania, the most frequently searched job titles are:
What job categories do people searching Patterned Learning Ai jobs in Pennsylvania look for? The top searched job categories for Patterned Learning Ai jobs in Pennsylvania are:
What cities in Pennsylvania are hiring for Patterned Learning Ai jobs? Cities in Pennsylvania with the most Patterned Learning Ai job openings:
Patterned Learning Ai jobs near you
Infographic showing various Patterned Learning Ai job openings in Pennsylvania as of August 2026, with employment types broken down into 1% As Needed, 70% Full Time, 25% Part Time, 1% Temporary, and 3% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

AI Enablement Lead

hajoca

Lafayette Hill, PA

Full-time

Posted 26 days ago

Hajoca rating

7.8

Company rating: 7.8 out of 10

Based on 59 frontline employees who took The Breakroom Quiz

142nd of 416 rated retail wholesalers

Job description

Are you a technology professional with a passion for artificial intelligence? Do you enjoy combining analytical thinking with strategic vision? Are you excited by the opportunity to lead and enable the use of AI across an entire organization? If so, then we’d like you to join our dedicated team as AI Enablement Lead.   

About the Role: 

The AI Enablement Lead leads the development and execution of AI enablement across Hajoca byestablishingguardrails, policies, and scalable processes that support responsible AI adoption. Partnering with business and technology leaders across the organization, the AI Enablement Lead evaluates AI tools and use cases while translating emerging technologies into clear, practical guidance. They are responsible for driving organization-wide awareness, training, and the sustained adoption of AI-enabled workflows while ensuring alignment across stakeholders to balance innovation with risk. 

In this role, you will: 

Build the Program

    • Help shape and execute Hajoca’s strategy for enabling responsible AI adoption across the business.

    • Establish and maintain practical guardrails — policies, review processes, intake flows, and training — that allow the business to move quickly with AI while managing risk appropriately.

    • Define what “good” looks like for AI usage at Hajoca and continuously evolve that definition as capabilities and the regulatory landscape change.

    • Document repeatable patterns, standards, and playbooks that improve the consistency and scalability of AI enablement across departments.
    • Define and track measures of success — adoption rates, usage trends, tool performance, and emerging risk signals — and present findings to the Sr. Manager and senior stakeholders to drive accountability and inform decisions.

Evaluate Use Cases & Establish Partnerships

    • Partner with business and technology leaders to evaluate proposed AI tools and use cases, identifying both opportunities and risks.

    • Serve as a trusted advisor to leaders considering AI investments — helping them frame problems, evaluate vendors, and structure pilots responsibly.

    • Translate prioritized use cases into implementation-ready materials: workflow definitions, process considerations, requirements, and clear acceptance criteria that implementation teams can act on.

    • Maintain visibility into AI activity across the company so the function can identify common patterns, scaling opportunities, and emerging risks.

Educate, Enable & Adopt Change

    • Develop and deliver AI awareness and training content for teammates at all levels — frontline, branch leadership, NSC, and executive audiences. Partner with the Learning Center team and Marketing & Communications to develop and distribute content that lands effectively at scale.

    • Lead targeted change adoption efforts in partnership with profit center leadership to drive effective, sustained use of AI-enabled workflows — not just initial rollout, but lasting behavior change.

    • Build a clear, accessible knowledge base of AI guidance, FAQs, and approved tools that teammates can rely on.

    • Stay current on AI capabilities, regulatory developments, and industry practices, and translate them into clear, practical guidance.

Partner Cross-Functionally on Risk & Vendors

    • Partner closely with the Manager, Cyber Security to ensure AI enablement and cyber security remain aligned on shared risks — data handling, third-party tools, and identity.

    • Partner with Procurement, Legal, and Information Security to oversee vendor relationships and contractual considerations for AI tools in use at Hajoca. Assess security, privacy, and compliance implications for new tools and ensure appropriate safeguards are in place prior to deployment.

    • Escalate vendor service issues and coordinate remediation with internal stakeholders as needed.

    • Coordinate with Legal, HR, and Procurement on AI-related contracting, policy, and acceptable use questions.

    • Partner with the Sr. Manager and Finance to maintain visibility into AI tool licensing and spend — tracking allocation across business units and ensuring the portfolio remains within budget parameters.

    • Partner with Middleware Engineering and the Data & Analytics team to ensure AI use cases access data through governed, well-understood pathways — aligning on integration patterns, data source of record, access controls, and appropriate use of enterprise data in AI-enabled workflows.
  • Successfully complete required safety and compliance training programs as assigned.
  • Perform other reasonably related duties as assigned by immediate supervisor and other management as requested.

About You: 

  • Bachelor's or Master’s degree in Computer Science, Data Science, Information Systems, Business, or a related field preferred.

  • 5 or more years of progressive experience in technology, technology risk, governance, consulting, product management, or a related field — with meaningful exposure to AI or emerging technology adoption.

  • Direct experience working with generative AI tools, AI platforms, or AI governance frameworks (e.g., NIST AI RMF, ISO/IEC 42001) preferred.

 

Our ideal candidate will also: 

  • Have a demonstrated ability to translate emerging technology concepts into clear business guidance for non-technical audiences.

  • Have experience working across business and technology stakeholders to develop practical policies, processes, or programs.

  • Have experience leading or supporting technology adoption initiatives, with an ability to drive sustained behavior change — not just launch and move on.

  • Demonstrate strong written and verbal communication skills, with the ability to write for executives, frontline teammates, and everyone in between.

  • Possess sound judgment, a builder’s mindset, and comfort operating in a function that is still being defined.

  • Have experience producing structured implementation materials — workflow designs, process documentation, requirements, or playbooks — in support of technology programs. 

  • Have a background in cyber security, IT risk, privacy, or compliance, in addition to AI.

  • Have experience with vendor evaluation, risk assessment, or technology contracting in an enterprise environment.

  • Be able to provide leadership through influence by establishing credibility, building strong relationships, facilitating collaboration, and driving results across cross-functional teams without direct supervisory authority.

  • Have experience in a multi-site or distributed business environment (distribution, retail, manufacturing, or similar).

  • Possess strong interpersonal skills to build relationships and lead discussions. 

  • Demonstrate leadership qualities—innovation, decisionmaking, mentoring, and influencing others.
  • Be able to work effectively in crossfunctional teams and adapt to changing requirements.

  • Be a quick learner who can master new technologies and collaborate effectively.

  • Be willing and able to travel, up to 15%

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