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Entry Level Aws Ai Practitioner Jobs (NOW HIRING)

MassMutual

AI Platform Engineer

Boston, MA · On-site

Relevant entry-level certifications are a plus but not required--for example AWS Certified Cloud Practitioner, AWS Solutions Architect - Associate, or CKAD. * Any hands-on experience with AI/ML ...

MassMutual

AI Platform Engineer

Springfield, MA · On-site

Relevant entry-level certifications are a plus but not required--for example AWS Certified Cloud Practitioner, AWS Solutions Architect - Associate, or CKAD. * Any hands-on experience with AI/ML ...

MassMutual

AI Platform Engineer

Manhattan, NY · On-site

Relevant entry-level certifications are a plus but not required--for example AWS Certified Cloud Practitioner, AWS Solutions Architect - Associate, or CKAD. * Any hands-on experience with AI/ML ...

Xenith Solutions

GenAI Developer

Leesburg, VA · Remote

$115K - $165K/yr

Technical certifications such as AWS Certified Developer and AWS AI Certified Practitioner * Experience with DevOps (CI/CD) solutions such as GitLab, etc. * Experience with AI/ML solutions or complex ...

Xenith Solutions LLC

GenAI Developer

Leesburg, VA · On-site +1

$115K - $165K/yr

Technical certifications such as AWS Certified Developer and AWS AI Certified Practitioner * Experience with DevOps (CI/CD) solutions such as GitLab, etc. * Experience with AI/ML solutions or complex ...

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How much do entry level aws ai practitioner jobs pay per hour?

As of Aug 9, 2026, the average hourly pay for entry level aws 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 is an entry level AWS AI practitioner?

Entry Level AWS AI Practitioners are professionals who are just beginning their careers in artificial intelligence (AI) and cloud computing, specifically using Amazon Web Services (AWS). They work with foundational AWS AI and machine learning (ML) services to help organizations implement basic AI solutions. Their responsibilities may include data preparation, training simple models, deploying AI services, and supporting more experienced data scientists and engineers. This role often requires knowledge of AWS tools like SageMaker, Rekognition, or Lex, and a basic understanding of programming and data analysis. Entry level practitioners typically work under supervision while gaining experience and AWS certifications.

What are the key skills and qualifications needed to thrive as an entry level AWS AI practitioner?

To thrive as an Entry Level AWS AI Practitioner, you need a foundational understanding of cloud computing, basic AI/ML concepts, and familiarity with programming languages such as Python, often supported by an AWS Cloud Practitioner or AWS Certified Machine Learning – Specialty certification. Experience with AWS services like SageMaker, Lambda, and S3, as well as basic data analysis tools, is typically required. Strong problem-solving skills, eagerness to learn, and effective communication set candidates apart in this role. These skills and qualities are vital for successfully implementing AI solutions on AWS and collaborating with technical teams in a fast-evolving environment.

What is the difference between Entry Level Aws Ai Practitioner vs Entry Level Aws Data Analyst?

AspectEntry Level Aws Ai PractitionerEntry Level Aws Data Analyst
CertificationsAWS Certified Machine Learning – Specialty, AWS Certified Cloud PractitionerAWS Certified Data Analytics – Specialty, AWS Certified Cloud Practitioner
Work EnvironmentDeveloping AI models, deploying machine learning solutions on AWSAnalyzing data sets, generating reports, visualizing data on AWS
Industry UsageAI and machine learning projects, AI-driven applicationsBusiness intelligence, data reporting, data-driven decision making

While both roles require AWS foundational knowledge and cloud certifications, the Entry Level Aws Ai Practitioner focuses on developing and deploying AI models, whereas the Entry Level Aws Data Analyst specializes in analyzing data and generating insights. The roles differ in their core tasks but share a common foundation in AWS cloud services.

What are some common challenges faced by entry level AWS AI practitioners, and how can they be addressed?

Entry Level AWS AI Practitioners often encounter challenges such as understanding complex cloud-native AI tools, managing resource costs, and collaborating effectively with cross-functional teams. Navigating AWS services like SageMaker, Lambda, and S3 can be overwhelming without hands-on practice. To overcome these obstacles, it's helpful to take advantage of AWS documentation, participate in team knowledge-sharing sessions, and seek mentorship from more experienced colleagues. Regularly working on small-scale projects and asking questions during code reviews can also accelerate skill development and integration into the team.
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Entry Level Aws Ai Practitioner jobs near you
Infographic showing various Entry Level Aws Ai Practitioner job openings in the United States as of August 2026, with employment types broken down into 76% Full Time, 8% Part Time, 8% Temporary, and 8% Contract. Highlights an 61% In-person, 8% Hybrid, and 31% Remote job distribution, with an average salary of $41,232 per year, or $19.8 per hour.

Federal AI Solutions Engineer (Entry Level)

A-TEK Inc.

Mclean, VA

$85K - $105K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 4 hours ago

Job description

A-TEK is seeking an early-career Federal AI Solutions Engineer to support the design, development, and deployment of mission-focused AI and cloud solutions across AWS and Azure environments. This role is ideal for recent graduates with a strong academic foundation in Artificial Intelligence, Machine Learning, software engineering, and cloud technologies who are eager to apply their skills to real-world federal mission challenges.

The engineer will work alongside senior architects and engineers to develop AI-enabled applications, cloud-native solutions, automation workflows, and rapid prototypes that support A-TEK's DigitalShift innovation initiatives.

This is a hybrid role based in McLean, VA. No visa sponsorship is available for this role. This role requires the ability to obtain and retain a public trust level security clearance.

Key Responsibilities

AI Solution Development

  • Assist in the design, development, and deployment of AI-powered applications and prototypes using:
    • AWS Bedrock
    • Azure OpenAI
    • LangChain, LlamaIndex, Semantic Kernel, CrewAI, or similar frameworks
  • Develop and test prompt engineering strategies, retrieval-augmented generation (RAG) workflows, and AI agent capabilities.
  • Support integration of AI solutions with APIs, enterprise systems, and cloud services.

Cloud Engineering

  • Build and maintain cloud-based environments in AWS and Azure.
  • Assist with infrastructure deployment using Infrastructure-as-Code tools such as Terraform, AWS CDK, or Bicep.
  • Support containerized deployments using ECS, EKS, or AKS.
  • Participate in CI/CD implementation and cloud automation efforts.

Technical Support & Innovation

  • Support senior engineers in troubleshooting cloud, AI, and data integration challenges.
  • Assist in developing reusable templates, accelerators, and reference architectures.
  • Participate in rapid prototyping efforts that demonstrate mission value for federal customers.

Collaboration & Knowledge Sharing

  • Collaborate with Cloud, Cybersecurity, Data Intelligence, and Agile Engineering teams.
  • Contribute to technical documentation, architecture diagrams, and knowledge-sharing initiatives.
  • Stay current with emerging AI, machine learning, and cloud technologies.

Security & Compliance

  • Support implementation of solutions that align with:
    • NIST AI Risk Management Framework (AI RMF)
    • FedRAMP requirements
    • Zero Trust principles
    • Secure coding and responsible AI practices

Required Qualifications

Education (Required)

Bachelor's degree in Computer Science with a concentration, specialization, minor, or significant coursework in Artificial Intelligence, Machine Learning, Data Science, or a closely related field.

Experience

  • 0-2 years of professional software engineering, AI/ML, or cloud development experience.
  • Relevant internships, research projects, capstone projects, graduate assistantships, or co-op experience may be substituted for professional experience.
  • Demonstrated programming experience in Python through coursework, projects, internships, or employment.

Technical Skills

  • Foundational understanding of machine learning, generative AI, and large language models.
  • Experience using cloud platforms (AWS or Azure) through coursework, internships, certifications, or projects.
  • Familiarity with:
    • REST APIs
    • Git version control
    • Containerization concepts
    • Data pipelines and databases
  • Understanding of prompt engineering, RAG concepts, or AI agents through academic or personal projects.
  • Strong analytical and problem-solving skills.

Certifications

One of the following is preferred within the first year of employment:

  • AWS Certified Cloud Practitioner or AWS Solutions Architect Associate
  • Microsoft Azure Fundamentals (AZ-900) or Azure AI Fundamentals (AI-900)

Preferred Qualifications

  • Academic or project experience with:
    • LangChain
    • LlamaIndex
    • Semantic Kernel
    • CrewAI
  • Exposure to vector databases such as Pinecone, Weaviate, FAISS, or Milvus.
  • Experience building AI, machine learning, or cloud-based capstone projects.
  • Familiarity with DevOps, MLOps, or CI/CD concepts.
  • Interest in federal government missions and emerging AI technologies.

Compensation

Salary Range

$85,000 - $105,000 annually

Salary will be determined based on education, certifications, internship experience, technical proficiency, and security clearance eligibility.

Benefits

  • Medical, Dental, and Vision Insurance
  • 401(k) with Employer Match
  • Paid Time Off and Federal Holidays
  • Professional Development and Certification Reimbursement
  • Career Growth and Mentorship Opportunities

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