AI Solutions Architect: responsibilities, education, skills and career path

Designs end-to-end AI solutions that align business needs with models and platforms.

Entry

Expert

Coding

High

Key skills

AI solution architectureML & LLM landscapeCloud AI platformsCost & scalability

Common progression

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Career overview

The AI Solutions Architect designs end-to-end AI solutions: translating business problems into AI architectures, selecting models and platforms, defining data, governance, cost and responsible-AI constraints. They bridge business, data science and engineering. The role leads to Solutions Architect, Enterprise Architect or CTO positions.

Main responsibilities

Design end-to-end technical solutions
Build and train machine learning models
Build internal self-service platforms for developers
Keep technical documentation up to date
Prepare and execute change requests in production
Analyse application logs to identify root causes
Coordinate the technical work of the team
Mentor junior team members and review their work
Own the technical roadmap of the perimeter

Technical skills

AI solution architecture92%

ML & LLM landscape88%

Cloud AI platforms88%

Data & governance82%

Responsible AI82%

Cost & scalability85%

Stakeholder management85%

Communication85%

Technologies

AWSGCPAzureSageMakerVertex AIAzure OpenAIOpenAI APILangChainPyTorchTensorFlowKubernetesTerraformMLflowPineconeKafkaSnowflakeGitHugging FaceDatabricks

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