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If you’ve Googled “Artificial Intelligence Engineer job description,” you’ve probably seen dozens of posts that look almost identical. Bullet points. Buzzwords. Copy-paste lists of responsibilities.
Here’s the problem: those posts don’t actually help you attract great AI engineers—they just give you generic filler content. And when you’re hiring for such a competitive, high-demand role, a bland job post won’t cut it.
Top AI talent isn’t swayed by boilerplate descriptions. They want to know what they’ll actually be building, why it matters, and who they’ll be working with. If your job post doesn’t inspire them, they’ll scroll right past you and take their skills somewhere else.
That’s why in this guide, we’re not just giving you another template. We’re going to break down what makes an AI Engineer job description effective—with real examples, human-friendly explanations, and two customizable templates you can use right away.
And if you want to go deeper into writing job posts that consistently attract top talent, check out our full guide on how to write a job post that attracts top talent , Link https://workscreen.io/how-to-write-a-job-post/ . But for now, let’s zero in on AI Engineers and how to write a post that stands out.
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What An Artificial Intelligence (AI) Engineer Actually Does - Their Roles Explained
An Artificial Intelligence (AI) Engineer is someone who builds smart systems that can learn, adapt, and solve problems. They take large amounts of data, design models that can understand patterns, and turn those models into real-world applications—like recommendation engines, fraud detection tools, chatbots, or self-driving car systems.
But it’s not just about writing algorithms. Great AI engineers are problem-solvers at heart. They need to understand business goals, work closely with product and engineering teams, and make sure the AI they build is practical, ethical, and scalable.
In short: an AI Engineer isn’t just a coder—they’re the bridge between advanced machine learning research and useful, everyday products that make a real impact.
Two Great Artificial Intelligence Engineer Job Description Templates
We’ll provide two tailored job description options:
1.✅ Option 1: For employers looking to hire an experienced candidates with prior experience.
2.Option 2: For employers open to hiring entry-level candidates or those willing to train someone with potential.
✅ Job Description Template #1 (Experienced AI Engineer)
Job Title: Senior Artificial Intelligence Engineer at NeuraTech Labs (Remote – US)
💼 Full-Time | 🌍 Remote (US-based) | 💵 $120,000 – $150,000 + Equity
📹 Meet the Team
Before you scroll down, watch this quick 90-second video from our CTO explaining why AI is at the heart of everything we build:
👉 [Insert Loom/YouTube Link]
About Us
At NeuraTech Labs, we’re building AI-driven solutions that help doctors diagnose faster and logistics teams optimize smarter. Founded in 2018, our mission is simple: take AI out of the lab and put it into the hands of people who can use it to save time, money, and lives.
We’re a team of engineers, data scientists, and product leaders who believe AI should solve real-world problems—not just academic ones. And now, we’re looking for an experienced AI Engineer to join us in scaling our platform.
What You’ll Do
- Design, train, and deploy machine learning models for healthcare and logistics use cases.
- Collaborate with data scientists, software engineers, and product managers to bring models into production.
- Optimize models for scalability, latency, and reliability.
- Stay up to date with the latest ML/AI research and apply it in practical ways.
- Mentor junior engineers and help shape technical decisions across projects.
What We’re Looking For
- 4+ years of hands-on experience in machine learning or AI engineering.
- Proficiency in Python and frameworks like TensorFlow, PyTorch, or Scikit-learn.
- Strong experience with data pipelines, cloud platforms (AWS, GCP, or Azure), and MLOps tools.
- Solid understanding of algorithms, deep learning architectures, and model evaluation.
- A pragmatic mindset—you balance cutting-edge research with practical product delivery.
Nice-to-haves
- Experience in healthcare or logistics.
- Published papers, Kaggle competition wins, or open-source contributions.
Why This Role Is Worth Your Time
At NeuraTech Labs, you won’t just be optimizing numbers in a spreadsheet—you’ll be building AI that helps doctors, nurses, and logistics teams make life-saving and efficiency-boosting decisions.
We offer:
- Competitive salary + meaningful equity.
- Health, dental, and vision insurance.
- Flexible working hours + fully remote setup.
- Annual learning stipend for conferences, books, or courses.
- 20 days of PTO + 10 company holidays.
How to Apply
We respect your time. That’s why we use WorkScreen—so you’re evaluated based on strengths, not buzzwords.
Click the link below to complete your short, structured evaluation:
👉 [Insert WorkScreen Link]
✅ Job Description Template #2 (Entry-Level / Willing-to-Train AI Engineer)
Job Title: Junior AI Engineer (Early Career) at NeuraTech Labs (Remote – US)
💼 Full-Time | 🌍 Remote (US-based) | 💵 $70,000 – $90,000 + Equity
📹 Meet the Team
Check out this 2-minute video from one of our AI Engineers sharing what it’s like to work on real-world projects here at NeuraTech Labs:
👉 [Insert Loom/YouTube Link]
About Us
At NeuraTech Labs, we’re on a mission to make AI practical and impactful. From helping hospitals reduce patient wait times to optimizing delivery routes for logistics companies, our AI products are designed to solve problems that matter.
We believe potential matters just as much as experience. That’s why we’re excited to bring on a Junior AI Engineer who’s eager to learn, grow, and make an impact.
What You’ll Do
- Work alongside senior engineers to design, train, and test AI models.
- Support data preprocessing, feature engineering, and model evaluation.
- Contribute to writing clean, maintainable code for production pipelines.
- Learn best practices in MLOps and cloud deployment.
- Participate in team research discussions and bring new ideas to the table.
What We’re Looking For
- Degree in Computer Science, Engineering, or related field (or equivalent experience).
- Solid Python skills and curiosity about ML/AI frameworks.
- Strong problem-solving ability and willingness to experiment.
- Good communicator who works well in a collaborative team.
Nice-to-haves
- Internship or academic experience in ML/AI projects.
- Familiarity with data visualization tools or cloud platforms.
Why This Role Is Worth Your Time
We know early-career roles can sometimes mean grunt work. Not here. At NeuraTech, you’ll be building meaningful projects while learning directly from senior engineers.
We offer:
- Competitive salary + early equity in a fast-growing company.
- Hands-on mentorship and structured learning paths.
- Access to conferences, certifications, and a $2,000 annual learning budget.
- Health, dental, and vision insurance.
- 18 days PTO + flexible schedule.
How to Apply
We respect your time. That’s why we use WorkScreen—so you’re evaluated based on strengths, not résumés alone.
Click the link below to complete your short, structured evaluation:
👉 [Insert WorkScreen Link]
Hiring doesn’t have to be hard.
If your hiring process is stressful, slow, or filled with second-guessing—WorkScreen fixes that. Workscreen helps you quickly identify top talent fast, eliminate low-quality applicants, and make better hires without the headaches.
Breakdown of Why These AI Engineer Job Posts Work
Writing a job description isn’t just about listing responsibilities. It’s about selling the opportunity to the right people. Here’s why the two AI Engineer job posts above are effective:
1. Clear, Specific Titles
Instead of just saying “AI Engineer,” the titles specify level and context:
- “Senior Artificial Intelligence Engineer at NeuraTech Labs (Remote – US)”
- “Junior AI Engineer (Early Career) at NeuraTech Labs (Remote – US)”
This matters because it tells candidates instantly what stage the role is (senior vs junior), the company name, and work location. No guesswork, no wasted clicks.
2. Warm Intros With Context
Both posts start with a team video and a human intro.
- For seniors, the CTO explains why AI matters to the company.
- For juniors, an engineer shares their personal experience.
This builds trust, makes the company feel approachable, and helps candidates visualize the people they’d work with—not just the tasks they’ll do.
3. Transparent Salary & Perks
Both versions clearly state pay ranges and benefits.
- Seniors see a $120k–$150k salary + equity.
- Juniors see a $70k–$90k salary + early equity + mentorship.
Transparency like this signals trustworthiness, avoids mismatched expectations, and filters out applicants who aren’t aligned with your compensation range.
4. Clear Responsibilities That Show Impact
Instead of generic bullets like “develop AI models,” the tasks are framed around real-world value:
- “Design, train, and deploy machine learning models for healthcare and logistics use cases.”
- “Work alongside senior engineers to design, train, and test AI models.”
This tells candidates why their work matters and how it connects to bigger goals. It’s not busywork—it’s meaningful.
5. Flexible Requirements
Both templates balance “must-haves” with “nice-to-haves.”
- The senior role expects 4+ years of experience but keeps industry background optional.
- The junior role emphasizes curiosity, problem-solving, and potential, while marking technical skills like cloud familiarity as “nice-to-have.”
This widens the talent pool and encourages good candidates to apply even if they don’t check every box.
6. Candidate-Respectful Hiring Process
Both posts explain that applications go through WorkScreen for fair, skill-based evaluation—not just résumé scanning.
This reassures candidates that they won’t be ghosted, that their application will actually be reviewed, and that they’ll be evaluated on merit. That alone sets your job post apart.
7. Human Tone That Connects
Notice how the language feels personal, not corporate.
- Phrases like “you won’t just be optimizing numbers in a spreadsheet” or “we know early-career roles can sometimes mean grunt work. Not here.” speak directly to candidates.
- It’s conversational and transparent—two things top candidates respect.
Example of a Bad Artificial Intelligence Engineer Job Description
Job Title: AI Engineer
Company: Tech Solutions Inc.
Location: Remote
Job Type: Full-Time
Job Summary
Tech Solutions Inc. is seeking an AI Engineer to design and implement artificial intelligence solutions. The ideal candidate will have strong technical skills, the ability to work independently, and knowledge of the latest AI tools and frameworks.
Key Responsibilities
- Develop and deploy AI models.
- Collaborate with team members.
- Maintain and update AI systems.
- Stay up to date with AI advancements.
Requirements
- Bachelor’s degree in Computer Science or related field.
- 3–5 years of experience in AI or machine learning.
- Proficiency in Python and AI frameworks.
- Strong problem-solving and communication skills.
How to Apply
Please submit your résumé and cover letter to careers@techsolutions.com by August 30, 2025. Only shortlisted candidates will be contacted.
❌ Why This Job Post Fails
- Generic Title
Just “AI Engineer.” It doesn’t specify seniority, context, or mission. A candidate scrolling LinkedIn has no reason to click. - Cold Intro
The job summary is bland and vague: “design and implement solutions.” No sense of purpose, no mention of what industries or problems they’re solving. - Responsibilities Are Too Broad
“Develop and deploy AI models” could mean anything. Candidates can’t picture their day-to-day work—or the impact of their work. - No Salary or Benefits
Leaving out compensation in 2025 is a red flag. Candidates expect transparency, and without it, many won’t bother applying. - Culture is Missing
There’s no mention of team values, work environment, or why the company exists. It feels like a faceless corporate listing. - Dismissive Hiring Process
“Only shortlisted candidates will be contacted” signals indifference and lack of respect. It makes candidates feel like just another number. - Zero Personality in the CTA
“Submit your résumé” is transactional. There’s no warmth, no excitement, no reason for a candidate to feel motivated to apply.
Bonus Tips to Make Your AI Engineer Job Post Stand Out
Even after you’ve written a clear, human, and compelling job description, there are a few small details that can elevate your post from “good” to “unforgettable.” These extras show candidates that you’ve thought carefully about their experience—and that you care about building trust right from the start.
1. Add a Security & Privacy Notice 🔒
Job scams are everywhere, and candidates know it. Including a short statement builds instant trust. For example:
“We take applicant privacy seriously. NeuraTech will never ask for payment, personal bank details, or financial information during the hiring process.”
This reassures candidates and makes your company look professional.
2. Mention Time Off or Flex Days 🌴
Yes, compensation matters—but so does rest. Candidates want to know you respect work-life balance. Instead of a vague “competitive benefits” line, add something like:
“Enjoy up to 20 paid vacation days + 10 company holidays each year to recharge and come back stronger.”
It’s a simple way to attract serious applicants.
3. Highlight Training & Growth Opportunities 📈
Top AI engineers want to grow as much as they want to work. Call this out directly:
“We invest in growth. You’ll have access to a $2,000 annual learning stipend for certifications, courses, and conferences—plus mentorship from senior engineers.”
This sets you apart from companies that only emphasize tasks, not long-term career growth.
4. Include a Loom or YouTube Video 🎥
Most job posts are walls of text. Break the pattern by embedding a short video from the hiring manager, CTO, or even a teammate.
This human touch gives candidates a face and voice to connect with before they even apply. It’s one of the easiest ways to build trust and authenticity.
Here is an example that we used in our master guide on how to write a great job post description , you can check it out here https://www.loom.com/share/ba401b65b7f943b68a91fc6b04a62ad4
Should You Use AI to Write Job Descriptions?
It feels like every platform these days has a “one-click AI job description generator.” It sounds tempting—just type in a job title, and boom, you’ve got a post in seconds.
But here’s the problem: when you let AI do all the work without giving it real context, you end up with generic, lifeless posts that don’t connect with serious candidates.
❌ Why You Shouldn’t Rely on AI Alone
- It produces filler. A post that reads like a Wikipedia summary doesn’t inspire engineers to apply.
- It attracts the wrong crowd. Generic posts pull in mass applicants, not selective, high-quality AI talent.
- It hurts your brand. Your job post is often the first impression a candidate gets. If it feels templated, so does your company.
✅ The Smarter Way to Use AI
AI isn’t the enemy—it’s a tool. But it only works if you provide the raw ingredients.
Here’s how to do it right:
- Feed it the essentials:
- What your company does
- The real responsibilities of the role
- Your culture and values
- Salary range and benefits
- What kind of person you’re actually looking for
- What your company does
- Prompt with context:
Example:
“Help me write a job description for our company, NeuraTech Labs. We’re hiring a Senior AI Engineer to design and deploy models for healthcare and logistics. Our culture is collaborative, mission-driven, and growth-oriented. We offer $120k–$150k, equity, health benefits, and a $2,000 annual learning stipend. We want to attract candidates who are curious, pragmatic, and motivated by impact. Here are my rough notes: [paste notes].” - Use AI for polishing, not replacing:
Let it refine your tone, improve clarity, and structure your content—but don’t let it write the entire post from scratch.
💡 Bottom line: AI can help you write a job description, but it shouldn’t own it. Candidates can spot a cookie-cutter listing instantly, and that’s the fastest way to lose top talent.
Build a winning team—without the hiring headache.
WorkScreen helps you hire fast, confidently, and without second-guessing.
Need Quick Copy-Paste Job Description Templates
Need a Quick Copy-Paste Job Description?
We get it—sometimes you just need something fast. Maybe you’ve already read through this guide and understand what a strong job post looks like, but you want a solid starting point to copy, paste, and customize.
That’s what these are.
✏️ Important Reminder:
Don’t copy this word-for-word and expect magic.
This is a foundation, not a final draft.
Add a Loom video, inject your team culture, and edit the details to reflect your actual company.
In this section, you’ll find two ready-to-use job description templates for quick copy-paste use — but please remember, like we mentioned above, don’t just copy them word-for-word and expect results.
Think of these as starting points, not final drafts.
- Option 1: A more conversational, culture-first job description that highlights personality and team fit.
- Option 2: A more structured format, including a Job Brief, Responsibilities, and Requirements for a traditional approach.
✅ Option 1: Conversational Job Description Template (Culture-First Style)
Job Title: Artificial Intelligence Engineer at [Company Name] (Remote – [Company Location])
💼 Full-Time | 💵 $XX – $XX + Equity
📹 Meet the Team
Check out this short video from our CTO on why AI is central to everything we build:
👉 [Insert Loom/YouTube Link]
About Us
At [Company Name], we believe AI should make life better—not more complicated. From helping doctors diagnose faster to streamlining logistics for global shippers, our products solve problems that matter.
We’re a small but growing team of engineers, data scientists, and product builders who care about impact over hype.
What You’ll Do
- Design, train, and deploy AI/ML models for healthcare and logistics.
- Collaborate with product teams to bring models into production.
- Optimize systems for scalability and performance.
- Stay curious and contribute new ideas to our research discussions.
What We’re Looking For
- X+ years of AI/ML experience (academic or industry).
- Strong Python skills + familiarity with TensorFlow/PyTorch.
- A problem-solver who values clarity, ethics, and practicality.
Nice-to-haves: Open-source contributions, Kaggle projects, or healthcare/logistics exposure.
Why Join Us
- $X–$X salary + early equity.
- Health, dental, and vision insurance.
- X PTO days + X company holidays.
- $XX annual learning budget (courses, conferences, certifications).
- A collaborative, mission-driven team where your work actually matters.
How to Apply
We respect your time. That’s why we use WorkScreen—so you’re evaluated on skills, not buzzwords.
👉 [Insert WorkScreen Link]
✅ Option 2: Structured Job Description Template (Job Brief + Responsibilities + Requirements)
Job Title: Artificial Intelligence Engineer
Company: NeuraTech Labs
Location: Remote (US)
Salary Range: $XX – $XX + Equity
Job Brief
[Company Name] is looking for an AI Engineer to help design and deploy machine learning solutions in healthcare and logistics. The ideal candidate combines strong technical skills with a problem-solving mindset and thrives in a collaborative, mission-driven environment.
Responsibilities
- Build and deploy ML models for healthcare and logistics use cases.
- Collaborate with engineers and product teams on production-ready solutions.
- Write clean, maintainable code and support MLOps pipelines.
- Research new methods and apply them pragmatically.
Requirements
- X+ years of experience in AI/ML engineering.
- Proficiency in Python + frameworks like PyTorch/TensorFlow.
- Experience with cloud platforms (AWS, GCP, or Azure).
- Strong analytical and problem-solving skills.
Perks & Benefits
- Salary: $X–$X + equity.
- Health, dental, vision insurance.
- X PTO days + X company holidays.
- $X/year learning stipend.
How to Apply
We use WorkScreen to make hiring faster and fairer. Apply through this link and complete a short evaluation:
👉 [Insert WorkScreen Link]
Why Use WorkScreen After Writing Your Job Post
A great job description is just the first step. Once candidates start applying, the real challenge begins: sorting through applications and figuring out who’s genuinely qualified.
That’s where WorkScreen.io comes in.
With WorkScreen, you can:
✅ Quickly spot your most promising candidates
WorkScreen automatically evaluates, scores, and ranks applicants on a performance-based leaderboard—making it easy to spot top talent, save time, and make smarter, data-driven hiring decisions.
✅ Go beyond résumés and buzzwords
Workscreen allows you to easily administer one-click skill tests. This way you can assess candidates based on real-world ability—not just credentials like résumés and past experience. This helps you hire more confidently and holistically.
✅ Filter out low-effort and AI-assisted applicants
Workscreen automatically eliminates low-effort applicants—including those who use AI Tools to apply, copy-paste answers, or rely on “one-click apply.” This way, you focus only on genuine, committed, and high-quality candidates—helping you avoid costly hiring mistakes.
smarter, faster, and with confidence.
💡 In short:
WorkScreen takes the heavy lifting off your plate so you can hire
👉Start with WorkScreen today
Frequently Asked Questions- AI Engineer Job Description
AI Engineers need a strong foundation in programming (Python is the most common), mathematics (linear algebra, probability, statistics), and machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn.
On top of technical ability, practical skills like data preprocessing, model deployment (MLOps), and cloud computing (AWS, GCP, Azure) are key. Soft skills also matter: problem-solving, teamwork, and communication are essential for turning technical solutions into real-world products.
Salaries vary depending on experience, location, and industry. In the U.S., entry-level AI
Engineers typically earn between $80,000–$100,000, while mid-level professionals average $110,000–$140,000. Senior AI Engineers, especially those with deep learning expertise, often make $150,000–$180,000+, with some roles in top tech hubs going even higher (sometimes $200k+ with bonuses or equity).
- Data Scientists focus more on analyzing data, building models, and generating insights.
- AI Engineers focus on turning those models into scalable, production-ready applications.
Think of Data Scientists as the “research and design” team, while AI Engineers handle “implementation and delivery.” Both roles overlap, but AI Engineers tend to have stronger software engineering and deployment skills.
AI Engineers are in demand across multiple sectors:
- Healthcare: diagnostic tools, medical imaging, patient outcome prediction.
- Finance: fraud detection, algorithmic trading, risk modeling.
- Retail & E-commerce: recommendation systems, personalized search.
- Logistics: route optimization, demand forecasting.
- Tech & SaaS: chatbots, generative AI, computer vision, NLP applications.
- Healthcare: diagnostic tools, medical imaging, patient outcome prediction.
There’s no fixed rule, but most startups benefit from 3–7 advisors. Too few, and you risk blind spots. Too many, and you lose focus. The goal is to build a balanced mix of expertise (fundraising, operations, marketing, industry-specific knowledge) rather than stacking your board with duplicates.
No. Unlike directors, advisors don’t carry fiduciary duties or legal liability for the company’s decisions. Their role is to advise, not to govern. This is one reason why advisory boards are so attractive to startups—they get strategic input without the complexity of formal governance.
