Job Description- Client is looking for a technical profile with a strong component of communication (simplification) and governance, not strictly an AI developer. The candidate must be hands-on with the platform (Anaconda Enterprise, Posit, AWS SageMaker, MLflow) and able to present AI capabilities to an executive audience.
- This dual mandate-platform operations and governance implementation across all business units-is what distinguishes this role from a purely technical one.
- Key recurring terms in the description highlight the true priorities: "ecosystem," "governance," "all business units," "executive stakeholders." The client is looking for someone who sees the AI platform as a shared service to evolve and structure, not as a one-time project.
- Experience in setting up an AI ecosystem (not just using AI tools) is the central priority.
Note: The client is likely targeting someone who has already operated an AI platform in a multi-team environment. A candidate familiar with cross-functional data environments will have a practical advantage for transversal governance.
Profiles to exclude:
- AI developers focused on modeling without platform.
- Cloud architects without an MLOpsfoundation.
- AI transformation consultants withouthands-on technical experience with client's listed tools
Requirements- Experience implementing an AI ecosystem. (Must have actually implemented, not just used)
- Strong knowledge of AI concepts, including executive-level communication. (Simplification is explicit)
- Mastery of software engineering best practices.
- Strong data engineering knowledge.
- Proficiency in Python and/or R. (Either is sufficient)
- Proficiency in AWS SageMaker or Azure AI. (Either is sufficient)
- Proficiency in Anaconda Enterprise or Posit (Either is sufficient)
- Proficiency in MLflow or Airflow (Either is sufficient)
Desired
- Knowledge of Snowflake and AWS S3(Representative)
- DevOps: GitHub, Jenkins, Kubernetes (Evaluate overall DevOps maturity)
- Strong AWS cloud ecosystem knowledge
Required
- 5+ years of experience
- Special projects: POCs, architecture validations, complex initiatives (explicitly required)
WHAT WE ARE LOOKING FOR
A profile such as an AI platform administrator or manager with at least 5 years of experience, who has already implemented or operated an AI ecosystem in production in a multi-team or cross-functional context.
The candidate must:
- Master at least one tool from eachcategory:
- SageMaker or Azure AI
- Anaconda Enterprise or Posit
- MLflow or Airflow
- Python or R
- Act as a technical reference for clients AI teams
- Establish governance rules across allbusiness units
- Present AI capabilities to executiveaudiences
The role also includes special initiatives: proof of concepts, architecture validations, complex projects.
Knowledge of data engineering (Snowflake, AWS S3) and DevOps (GitHub, Jenkins, Kubernetes) is desirable.
Experience in insurance or financial services is an asset but not required.
WHAT WE DO NOT WANT
- Profiles focused on modeling/datascience without AI platform operations experience
- Less than 5 years of experience in AIand software engineering
- No hands-on experience with at least oneof client's named tools
- No experience building shared ormulti-team AI ecosystems
- Inability to simplify and present AIconcepts to executive stakeholders
