Building an AI Team: First 5 Hires That Matter

martin3127
Jan 7
2 min read

Building an AI team from scratch can feel like navigating a maze. There are countless roles, technologies, and approaches but not every hire matters equally in the early stages.

At Raice AI Recruitment, we help companies prioritize the right talent to turn AI strategies into reality. Here are the first five hires that truly matter when building an AI team in 2026.

1. AI/ML Engineer

Your first hire should be someone who can turn prototypes into production-ready systems.

Why it matters:

Ensures models are scalable and reliable
Bridges the gap between data experimentation and product delivery
Establishes coding, testing, and deployment standards

Skills to prioritise:

Python, ML frameworks, cloud deployment
MLOps, CI/CD pipelines
Production model monitoring and optimization

2. Data Engineer

Data is the backbone of any AI system. A skilled Data Engineer ensures your models have clean, structured, and reliable data.

Why it matters:

Builds pipelines for real-time and batch data
Maintains data quality, governance, and compliance
Enables data scientists and engineers to work efficiently

Skills to prioritise:

SQL, ETL, data warehousing
Cloud platforms (AWS, GCP, Azure)
Data pipeline orchestration (Airflow, dbt)

3. Data Scientist / Applied AI Specialist

Once data pipelines are in place, you need someone to turn data into insights and models.

Why it matters:

Builds predictive models and experiments
Identifies high-impact AI opportunities
Communicates findings to business stakeholders

Skills to prioritise:

Statistics, ML, NLP/GenAI depending on focus
Experimentation design and evaluation metrics
Strong communication and domain knowledge

4. AI Product Manager

AI projects fail without someone who can align technology with business value.

Why it matters:

Bridges technical teams and business stakeholders
Prioritises features and use cases based on ROI
Ensures AI systems solve real problems and gain adoption

Skills to prioritise:

Product lifecycle management
AI knowledge and technical literacy
Strong stakeholder communication

5. AI Lead / Architect

The final early hire should provide technical leadership and strategic direction.

Why it matters:

Sets architecture and best practices
Mentors junior team members
Oversees system reliability, compliance, and scalability

Skills to prioritise:

System design for AI at scale
Understanding of ML, MLOps, and data architecture
Risk management and responsible AI practices

Building the Core AI Team

These five roles create a balanced AI nucleus capable of moving from strategy to execution:

AI/ML Engineer: builds and deploys
Data Engineer: ensures data quality
Data Scientist/Applied AI Specialist: extracts insights
AI Product Manager: aligns with business goals
AI Lead/Architect: guides technical strategy

Early hires should focus on versatility and collaboration. In 2026, the AI landscape changes fast, and adaptable talent is the best hedge against obsolescence.

Raice AI Recruitment Perspective

We help organisations identify and attract candidates who can turn AI vision into reality. Early hires are critical as they set the foundation for every future AI project.

Building an AI team is not just about filling roles, it’s about building capability that scales.

Final Thought: The first five hires define your AI team’s potential. Hire strategically, and your AI strategy won’t stay on PowerPoint slides it will deliver real-world impact.

Raice AI Recruitment partners with companies ready to build AI teams that execute.