Hire Artificial Intelligence Developers
Connect with skilled Artificial Intelligence Developers from Latin America. Fluent in NLP, vision models, and deployment with full setup in 21 days.
Hire Remote Artificial Intelligence Developers
Marco is an AI professional developing structured and intelligent tech-driven solutions.
- AI Systems
- Technical Architecture
- Data Modeling
- System Integration
- Scalability
Fernanda is an AI strategist aligning smart technologies with product development.
- AI Strategy
- Tech Roadmapping
- Model Testing
- System Evaluation
- Cross-functional Planning
Yuliana is an AI expert designing intelligent systems that learn, adapt, and evolve.
- AI Development
- Model Optimization
- Ethical AI
- Technical Documentation
- Model Deployment
Renata is an AI expert turning innovation into intelligent, people-focused systems.
- AI Systems
- Data Engineering
- Predictive Modeling
- API Integration
- Tech Strategy
Daniel is an AI specialist crafting intelligent systems with practical user value.
- Model Training
- AI Architecture
- Data Engineering
- API Integration
- AI Product Development
Malena is an AI expert focused on building intelligent tools with lasting user value.
- AI Systems Development
- Machine Learning Models
- Data Pipeline Design
- Python & TensorFlow
- Problem Solving with AI
Sebastián excels in prompt engineering, blending creativity and precision seamlessly.
- NLP
- Python
- AI Ethics
- Data Labeling
- LLMs
"Over the course of 2024, we successfully hired 9 exceptional team members through Lupa, spanning mid-level to senior roles. The quality of talent has been outstanding, and we’ve been able to achieve payroll cost savings while bringing great professionals onto our team. We're very happy with the consultation and attention they've provided us."
“We needed to scale a new team quickly - with top talent. Lupa helped us build a great process, delivered great candidates quickly, and had impeccable service”
“With Lupa, we rebuilt our entire tech team in less than a month. We’re spending half as much on talent. Ten out of ten”
Lupa's Proven Process
Together, we'll create a precise hiring plan, defining your ideal candidate profile, team needs, compensation and cultural fit.
Our tech-enabled search scans thousands of candidates across LatAm, both active and passive. We leverage advanced tools and regional expertise to build a comprehensive talent pool.
We carefully assess 30+ candidates with proven track records. Our rigorous evaluation ensures each professional brings relevant experience from industry-leading companies, aligned to your needs.
Receive a curated selection of 3-4 top candidates with comprehensive profiles. Each includes proven background, key achievements, and expectations—enabling informed hiring decisions.
Reviews
"Over the course of 2024, we successfully hired 9 exceptional team members through Lupa, spanning mid-level to senior roles. The quality of talent has been outstanding, and we’ve been able to achieve payroll cost savings while bringing great professionals onto our team. We're very happy with the consultation and attention they've provided us."
“We needed to scale a new team quickly - with top talent. Lupa helped us build a great process, delivered great candidates quickly, and had impeccable service”
“With Lupa, we rebuilt our entire tech team in less than a month. We’re spending half as much on talent. Ten out of ten”
“We scaled our first tech team at record speed with Lupa. We couldn’t be happier with the service and the candidates we were sent.”
"Recruiting used to be a challenge, but Lupa transformed everything. Their professional, agile team delivers top-quality candidates, understands our needs, and provides exceptional personalized service. Highly recommended!"
“Lupa has become more than just a provider; it’s a true ally for Pirani in recruitment processes. The team is always available to support and deliver the best service. Additionally, I believe they offer highly competitive rates and service within the market.”
"Highly professional, patient with our changes, and always maintaining clear communication with candidates. We look forward to continuing to work with you on all our future roles."
“Lupa has been an exceptional partner this year, deeply committed to understanding our unique needs and staying flexible to support us. We're excited to continue our collaboration into 2025.”
"What I love about Lupa is their approach to sharing small, carefully selected batches of candidates. They focus on sending only the three most qualified individuals, which has already helped us successfully fill 7 roles.”
"We hired 2 of our key initial developers with Lupa. The consultation was very helpful, the candidates were great and the process has been super fluid. We're already planning to do our next batch of hiring with Lupa. 5 stars."
"Working with Lupa for LatAm hiring has been fantastic. They found us a highly skilled candidate at a better rate than our previous staffing company. The fit is perfect, and we’re excited to collaborate on more roles."
"We compared Lupa with another LatAm headhunter we found through Google, and Lupa delivered a far superior experience. Their consultative approach stood out, and the quality of their candidates was superior. I've hired through Lupa for both of my companies and look forward to building more of my LatAm team with their support."
“We’ve worked with Lupa on multiple roles, and they’ve delivered time and again. From sourcing an incredible Senior FullStack Developer to supporting our broader hiring needs, their team has been proactive, kind, and incredibly easy to work with. It really feels like we’ve gained a trusted partner in hiring.”
Working with Lupa was a great experience. We struggled to find software engineers with a specific skill set in the US, but Lupa helped us refine the role and articulate our needs. Their strategic approach made all the difference in finding the right person. Highly recommend!
Lupa goes beyond typical headhunters. They helped me craft the role, refine the interview process, and even navigate international payroll. I felt truly supported—and I’m thrilled with the person I hired. What stood out most was their responsiveness and the thoughtful, consultative approach they brought.
Artificial Intelligence Developers Soft Skills
Creative Thinking
Innovate with AI tools to solve real-world problems.
Systems Thinking
Understand how models integrate into full applications.
Team Communication
Share insights and blockers clearly across functions.
Problem Solving
Design practical AI solutions with limited resources.
Initiative
Take ownership of research and prototyping efforts.
Precision
Focus on detail when integrating complex AI systems.
Artificial Intelligence Developers Skills
AI System Design
Architect intelligent systems for prediction and automation.
NLP & Computer Vision
Develop AI apps using text and image processing models.
Model Integration
Embed trained models into live applications and systems.
Inference Pipelines
Build efficient pipelines for real-time model predictions.
Framework Proficiency
Work with TensorFlow, PyTorch, Keras, and related tools.
Algorithm Design
Implement AI logic suited to specific product use cases.
How to Write an Effective Job Post to Hire Artificial Intelligence Developers
Recommended Titles
- AI Engineer
- AI Software Developer
- Intelligent Systems Developer
- AI Platform Engineer
- ML/AI Developer
- Deep Learning Developer
Role Overview
- Tech Stack: Proficient in Python, OpenCV, spaCy, and cloud AI services (AWS, GCP).
- Project Scope: Develop end-to-end AI solutions for automation, NLP, and computer vision.
- Team Size: Work cross-functionally with data, dev, and product teams (5–8 people).
Role Requirements
- Years of Experience: Minimum of 4 years in AI solution design and development.
- Core Skills: Algorithm implementation, model integration, and API design.
- Must-Have Technologies: Python, NumPy, TensorFlow, AWS AI/ML, Docker.
Role Benefits
- Salary Range: $105,000 – $160,000 depending on experience and location.
- Remote Options: Global remote flexibility with core collaboration hours.
- Growth Opportunities: Exposure to production-grade AI systems and research translation.
Do
- Detail experience across ML, DL, and AI system integration
- Include role in cross-functional AI product teams
- Mention exposure to real-time and adaptive AI systems
- Highlight advancement in applied AI development
- Use strategic and forward-looking job phrasing
Don't
- Don’t bundle ML, DL, and AI without distinction
- Avoid listing tools without use-case context
- Don’t ignore cross-functional collaboration needs
- Refrain from only listing responsibilities, not outcomes
- Don’t use ambiguous titles like “AI Specialist”
Top Artificial Intelligence Developer Interview Questions
How to evaluate Artificial Intelligence Developer skills
What AI techniques have you implemented in production?
Look for applied knowledge in NLP, CV, or recommendation systems. Bonus if they’ve deployed real-time or large-scale AI systems.
Can you describe your experience with neural networks?
Expect familiarity with architecture types like CNNs, RNNs, Transformers. They should explain choices based on task requirements.
How do you ensure AI systems are explainable and trustworthy?
Listen for mention of SHAP, LIME, model audits, or ethical AI frameworks. Bonus if they’ve worked on bias reduction or transparency tools.
What frameworks or tools do you use for AI development?
Answers should include TensorFlow, PyTorch, Hugging Face, or OpenAI APIs. Look for depth of use, not just tool names.
What’s your approach to data preprocessing for AI models?
Look for mention of cleaning, normalization, tokenization, augmentation, and how preprocessing aligns with model architecture.
How do you approach solving an AI problem with unclear success criteria?
Expect stakeholder interviews, defining proxy KPIs, and iterative refinement of the problem scope.
Describe a time you had to pivot your AI solution mid-project.
They should share how they re-evaluated assumptions, adapted models, or changed data pipelines.
How do you debug low performance in AI prototypes?
Look for dataset inspection, model evaluation granularity, or modular testing strategies.
What’s your strategy when compute constraints limit model choice?
Expect experience with model compression, distillation, or edge-compatible architectures.
How do you validate an AI system in a real-world environment?
Look for A/B testing, user feedback loops, or simulation frameworks for safety and validation.
Describe a time you had to advocate for a complex AI approach.
Look for persuasive communication, stakeholder education, and technical simplification.
Tell me about a project where alignment with business goals was unclear.
Expect proactive clarification, product alignment, and prioritization of technical effort.
How do you navigate tensions between performance and fairness in AI systems?
Expect awareness of ethical balance, testing strategies, and responsible defaults.
Describe a time when team feedback changed your implementation plan.
Look for openness, collaboration, and evidence-driven decision-making.
What’s your approach when your work is misunderstood by non-technical teams?
Expect empathy, analogies, and shared outcomes to bridge the gap.
- Overuse of black-box models without explainability
- Lack of practical AI deployment experience
- Vague understanding of model lifecycle
- Poor cross-functional collaboration habits
- Overlooking edge cases in AI systems
Build elite teams in record time, full setup in 21 days or less.
Book a Free ConsultationWhy We Stand Out From Other Recruiting Firms
From search to hire, our process is designed to secure the perfect talent for your team
Local Expertise
Tap into our knowledge of the LatAm market to secure the best talent at competitive, local rates. We know where to look, who to hire, and how to meet your needs precisely.
Direct Control
Retain complete control over your hiring process. With our strategic insights, you’ll know exactly where to find top talent, who to hire, and what to offer for a perfect match.
Seamless Compliance
We manage contracts, tax laws, and labor regulations, offering a worry-free recruitment experience tailored to your business needs, free of hidden costs and surprises.
Lupa will help you hire top talent in Latin America.
Book a Free Consultation
Top Artificial Intelligence Developer Interview Questions
How to evaluate Artificial Intelligence Developer skills
What AI techniques have you implemented in production?
Look for applied knowledge in NLP, CV, or recommendation systems. Bonus if they’ve deployed real-time or large-scale AI systems.
Can you describe your experience with neural networks?
Expect familiarity with architecture types like CNNs, RNNs, Transformers. They should explain choices based on task requirements.
How do you ensure AI systems are explainable and trustworthy?
Listen for mention of SHAP, LIME, model audits, or ethical AI frameworks. Bonus if they’ve worked on bias reduction or transparency tools.
What frameworks or tools do you use for AI development?
Answers should include TensorFlow, PyTorch, Hugging Face, or OpenAI APIs. Look for depth of use, not just tool names.
What’s your approach to data preprocessing for AI models?
Look for mention of cleaning, normalization, tokenization, augmentation, and how preprocessing aligns with model architecture.
How do you approach solving an AI problem with unclear success criteria?
Expect stakeholder interviews, defining proxy KPIs, and iterative refinement of the problem scope.
Describe a time you had to pivot your AI solution mid-project.
They should share how they re-evaluated assumptions, adapted models, or changed data pipelines.
How do you debug low performance in AI prototypes?
Look for dataset inspection, model evaluation granularity, or modular testing strategies.
What’s your strategy when compute constraints limit model choice?
Expect experience with model compression, distillation, or edge-compatible architectures.
How do you validate an AI system in a real-world environment?
Look for A/B testing, user feedback loops, or simulation frameworks for safety and validation.
Describe a time you had to advocate for a complex AI approach.
Look for persuasive communication, stakeholder education, and technical simplification.
Tell me about a project where alignment with business goals was unclear.
Expect proactive clarification, product alignment, and prioritization of technical effort.
How do you navigate tensions between performance and fairness in AI systems?
Expect awareness of ethical balance, testing strategies, and responsible defaults.
Describe a time when team feedback changed your implementation plan.
Look for openness, collaboration, and evidence-driven decision-making.
What’s your approach when your work is misunderstood by non-technical teams?
Expect empathy, analogies, and shared outcomes to bridge the gap.
- Overuse of black-box models without explainability
- Lack of practical AI deployment experience
- Vague understanding of model lifecycle
- Poor cross-functional collaboration habits
- Overlooking edge cases in AI systems
