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AI Practitioner/Forward Deployed Engineer

The AI Practitioner (Enterprise GPT Platform) is a hands-on, customer-facing role on the Enterprise Insights & GPT Platform team. You will design, build, and run production AI applications on our ...

Northbridge University

PR · On-site

AWS Certified AI Practitioner * Microsoft Certified: Azure AI Fundamentals * Microsoft Certified: Power BI Data Analyst Associate * Artificial Intelligence Governance Professional (AIGP) * Project ...

h2o.ai

Technical Program Manager

Charlotte, NC · On-site

$126K - $163.10K/yr

You will be expected to speak the language of AI practitioners, challenge customers to think bigger, and leverage AI tools yourself to accelerate program delivery, generate insights, and communicate ...

h2o.ai

Technical Program Manager

Charlotte, NC · On-site

$126K - $163.10K/yr

You will be expected to speak the language of AI practitioners, challenge customers to think bigger, and leverage AI tools yourself to accelerate program delivery, generate insights, and communicate ...

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How much do ai practitioner jobs pay per hour?

As of Jun 1, 2026, the average hourly pay for ai practitioner in the United States is $19.82, according to ZipRecruiter salary data. Most workers in this role earn between $17.31 and $21.15 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an AI Practitioner, and why are they important?

To thrive as an AI Practitioner, you need strong analytical skills, a solid grounding in mathematics and statistics, and experience with programming languages like Python, often supported by a degree in computer science or a related field. Familiarity with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and certifications like TensorFlow Developer or AWS Certified Machine Learning are highly valuable. Critical thinking, problem-solving, and effective communication set outstanding practitioners apart by enabling them to translate complex models into actionable business solutions. These skills and qualities are vital for developing robust AI systems that address real-world challenges and deliver measurable impact.

What are some common challenges AI Practitioners face when integrating machine learning solutions into existing business processes?

AI Practitioners often encounter challenges such as aligning machine learning models with business objectives, ensuring data quality and availability, and managing stakeholder expectations. Integrating AI solutions typically requires close collaboration with cross-functional teams, including IT, product managers, and subject matter experts, to ensure seamless deployment and adoption. Additionally, maintaining transparency and explainability of AI models can be crucial for gaining trust from non-technical stakeholders and meeting compliance requirements.

What are AI Practitioners?

AI Practitioners are professionals who specialize in designing, developing, and implementing artificial intelligence solutions. Their work involves applying machine learning, data analysis, and advanced algorithms to solve real-world problems across various industries. They often collaborate with data scientists, engineers, and business leaders to create intelligent systems that can automate tasks, extract insights from data, and improve decision-making processes. AI Practitioners typically have expertise in programming, mathematics, and statistics, as well as experience with AI frameworks and tools.

What is the difference between Ai Practitioner vs Data Scientist?

AspectAi PractitionerData Scientist
Required CredentialsCertifications in AI, machine learning, programming skillsStatistics, programming, data analysis certifications
Work EnvironmentDeveloping AI models, implementing algorithms, working with AI toolsAnalyzing data, building predictive models, interpreting data insights
Employer & Industry UsageTech companies, AI startups, R&D departmentsFinance, healthcare, tech firms, research institutions

While both roles involve working with data and algorithms, an Ai Practitioner primarily focuses on developing and deploying AI solutions, whereas a Data Scientist emphasizes analyzing data to extract insights and build predictive models. The roles often overlap but differ in their core focus and skill sets.

More about Ai Practitioner jobs
What cities are hiring for Ai Practitioner jobs? Cities with the most Ai Practitioner job openings:
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Ai Practitioner jobs near you
Infographic showing various Ai Practitioner job openings in the United States as of May 2026, with employment types broken down into 74% Full Time, 25% Part Time, and 1% Contract. Highlights an 99% Physical, and 1% Remote job distribution, with an average salary of $41,232 per year, or $19.8 per hour.

Gen AI Practitioner- Azure Stack

HMG America

Manhattan, NY • Hybrid

Other

Posted 3 days ago

Job description

HMG America LLC is the best Business Solutions focused Information Technology Company with IT consulting and services, software and web development, staff augmentation and other professional services. One of our direct clients is looking for Gen AI Practitioner- Azure Stack in NYC . Below is the detailed job description.

Title: Gen AI Practitioner- Azure Stack

Location: Hybrid in NYC

Duration: FTE

Job Description:

Role Overview
Work with the client to design and implement enterprise Generative AI solutions on Microsoft Azure, leveraging large language models and modern data platforms to deliver AI-driven applications such as copilots, document intelligence, and conversational interfaces.

Key Responsibilities

  • Strategize and develop GenAI solutions using Azure OpenAI Service and Azure AI Studio.
  • Implement Retrieval-Augmented Generation (RAG) using Azure AI Search and enterprise data sources.
  • Build AI-enabled applications and APIs using Python and orchestration frameworks such as LangChain.
  • Integrate GenAI solutions with cloud data platforms like Azure Synapse Analytics and Azure Data Lake.
  • Support AI governance, model evaluation, and responsible AI practices in enterprise environments.

Skills

  • Experience building GenAI / LLM applications.
  • Strong knowledge of Azure AI and data services
  • Strong stakeholder management and communications skills
  • Proficiency in Python and API-based development.
  • Familiarity with RAG architectures, vector search, and prompt engineering.

Apply