AI Engineer Job Description: Qualifications and Responsibilities

How to Write an AI Engineer Job Description

Hiring an AI Engineer means finding someone who can do more than build models. A good job description shows candidates the kind of work they’ll be doing, what tools they'll need to know, and how their role fits into the bigger picture. It’s also a chance to make your team’s work stand out in a field that’s changing fast.

What is an AI Engineer / What does an AI Engineer do?

AI Engineers develop intelligent systems that learn from data and improve over time. Their work often includes designing algorithms, training machine learning models, and working with other teams to bring those models into real products. They may focus on areas like natural language processing, computer vision, or predictive analytics.

The importance of a good AI Engineer Job Description

A clear job description makes the hiring process smoother from the start. It helps applicants figure out if they’re the right fit, and it saves hiring teams time by setting the right expectations. Especially in AI, where roles can vary, it’s important to be specific about the tools, experience, and outcomes you're looking for.

AI Engineer Job Description Template

About the role and the team:
We’re looking for an AI Engineer to work on building models that improve how we solve problems with data. You’ll be part of a small technical team that collaborates closely with product managers, engineers, and data scientists. The work ranges from prototyping ideas to deploying models that support real business goals.

Education & Training:

• Required education: Bachelor’s degree in Computer Science, AI, or another technical field
  
• Preferred education: Master’s or PhD in Machine Learning, Data Science, or a related subject; certifications in TensorFlow or cloud AI tools
  

What you’ll be doing:

• Design and train models for tasks like classification, recommendations, or forecasting
  
• Integrate AI features into applications alongside engineers and product teams
  
• Explore ways to improve model accuracy and reliability over time
  
• Document your work and contribute to internal best practices
  
• Support automation workflows by contributing to MLOps pipelines
  

Skills Requirement:

• Technical skills: Python or Java programming, experience with TensorFlow or PyTorch, and some familiarity with cloud tools like AWS SageMaker or Google AI Platform
  
• Non-technical skills: Ability to explain your work, work well in a team, and stay organized
  
• Preferred (but not required): Background in NLP or generative models, contributions to open-source, or experience working with LLMs
  

AI Engineer Pay & Benefits

The average salary for AI Engineers in the U.S. is around $145,000, with most roles falling between $120,000 and $170,000. Some organizations may also offer:

• Equity or stock option plans
  
• Flexible hours or hybrid/remote setups
  
• Paid travel for conferences and ongoing learning
  
• Access to high-performance computing or research tools
  

Tailoring your AI Engineer Job Description

Common sub-types of AI Engineer roles

• Applied AI Engineer: Focuses on using AI to solve business problems
  
• NLP Engineer: Works with language models and conversational tools
  
• Computer Vision Engineer: Handles image classification, detection, and tracking
  
• AI Research Engineer: Explores experimental models and writes research
  

Adjusting for seniority

• Junior (0–2 years): Experience with academic projects or internships
  
• Mid-Level (2–5 years): Comfortable building and deploying models independently
  
• Senior (5+ years): Leads model design, mentors others, and contributes to roadmap decisions
  

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