Builds and ships AI features: model integration, APIs and production AI systems.
Entry
Senior
Coding
Very High
Key skills
Common progression
- Data Scientist
- AI Engineer
- Senior AI Engineer
Career overview
The AI Engineer turns models into production AI features: integrating LLMs and ML models into applications, building APIs, orchestration, evaluation and guardrails. They bridge data science and software engineering. The role leads to Senior AI Engineer, AI Solutions Architect or Machine Learning Engineer positions.
Main responsibilities
- Build and train machine learning models
- Serve model inference at scale
- Design and document REST APIs
- Write, test and review production code
- Build and maintain CI/CD pipelines
- Monitor platform health, alerts and dashboards
- Keep technical documentation up to date
- Prepare and execute change requests in production
- Analyse application logs to identify root causes
- Mentor junior team members and review their work
Technical skills
Technologies
Education level
Education requirements vary depending on the company, country and experience. Professional experience, certifications and technical skills can sometimes compensate for formal education.
High School / Bac
Less common
Bac+2 (2-year degree)
Less common
Bac+3 (Bachelor)
Less common
Bac+5 (Master / Engineering)
Common entry point
Experience & coding level
Experience level
Coding level
Useful certifications
Certifications are never mandatory. They are one way among others to prove a skill.
- Microsoft AI Engineer Associate (AI-102)
- Google Professional ML Engineer
- AWS Machine Learning Specialty
Where can this career take you?
Multiple paths are possible. Click a role to open its profile.
Direct progression
Possible branches
Where can you go next?
Realistic next career moves, with compatibility and a transition roadmap for each.
Overlap: 50% · Difficulty: Easy
Skills to learn: RAG & agents, Fine-tuning / LoRA, Vector databases
View roadmapOverlap: 38% · Difficulty: Medium
Skills to learn: Machine learning, MLOps, PyTorch / TensorFlow
View roadmapOverlap: 12% · Difficulty: Medium
Skills to learn: AI solution architecture, ML & LLM landscape, Data & governance
View roadmapWhere can you go from here?
A typical progression built from real career relationships. Click any role to open its profile.
- Data Scientist
- AI Engineer
- Senior AI Engineer
Soft skills
- Problem solving
- Technical curiosity
- Analytical thinking
- Clear communication
- Sense of ownership
- Teamwork
Common previous careers
Roles that frequently lead into this career.
Overlap: 38% · Difficulty: Medium
Skills to learn: AI / LLM integration, API design, Model serving
View roadmapOverlap: 24% · Difficulty: Easy
Skills to learn: AI / LLM integration, API design, Prompt engineering
View roadmapOverlap: 37% · Difficulty: Medium
Skills to learn: AI / LLM integration, API design, Prompt engineering
View roadmapRelated resources
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A documented transition from this role to the next.
AI EngineerGenerative AI Engineer
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