NavitasPartners
Brampton, ON
Fermé
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Détails de l'emploi :
Télétravail
Temps plein
Expérimenté
Responsible AI & Governance Lead – Enterprise AI Platforms
Location: US / Canada (Remote/Hybrid)
Type: Contract / Full-Time
Overview:
We are seeking a Responsible AI & Governance Lead to drive ethical, compliant, and scalable AI adoption across enterprise data platforms. This role will ensure AI systems align with regulatory standards and business objectives.
Key Responsibilities:
- Define and implement Responsible AI frameworks and governance models
- Establish AI risk management, compliance, and audit processes
- Collaborate with engineering, data, and business teams to embed governance
- Ensure scalability, transparency, and fairness across AI solutions
Required Skills:
- Strong experience in AI governance, compliance, or risk frameworks
- Cloud platform exposure (AWS, Azure, GCP)
- Hands-on experience implementing governance in AI/ML systems
Nice to Have / Coverage:
- Data Engineering: Databricks, Snowflake, Azure Synapse, BigQuery
- ML/AI Engineering: Python, PyTorch, MLOps, LangChain
- Cloud Architecture: AWS, Azure, GCP (aligned with hyperscaler ecosystems)
- GenAI & Agentic AI: Governance for LLMs and autonomous AI systems
For more details reach at [email protected].
Foire aux questions
The role focuses on driving ethical, compliant, and scalable AI adoption across enterprise data platforms, ensuring AI systems align with regulatory standards and business objectives.
This position is based in the US/Canada with remote or hybrid work options.
Key responsibilities include defining and implementing Responsible AI governance, establishing AI risk management and audit processes, collaborating with cross-functional teams to embed governance, and ensuring transparency and fairness in AI solutions.
The role requires strong experience in AI governance, compliance, or risk frameworks, and hands-on experience implementing governance in AI/ML systems, with cloud platform exposure (AWS, Azure, GCP).
Nice-to-have skills include data engineering tools like Databricks, Snowflake, Azure Synapse, BigQuery; ML/AI engineering with Python, PyTorch, MLOps, LangChain; and GenAI/governance for LLMs and autonomous AI systems.
For more details, reach out via [email protected].
