Sr. AI Engineer - R01572484
About The Position
The Sr. AI Engineer leads the design and architecture of end-to-end enterprise AI platforms, ensuring scalability, reliability, and operational readiness. The role defines and implements frameworks for model lifecycle management, MLOps/LLMOps, AI observability, and operationalization, while establishing Responsible AI principles, governance frameworks, and technical guardrails for compliant and ethical AI deployment. The engineer drives platform-level technical decisions and provides architectural leadership across business, data, technology, and platform teams to turn AI strategy into production-ready solutions. The role evaluates emerging AI technologies, guides teams in selecting models, platforms, frameworks, and architectural patterns, and collaborates with senior stakeholders on the enterprise AI roadmap and platform strategy.
Requirements
- At least 7 years of experience in data science and AI, including significant leadership in designing and operationalizing enterprise-scale AI platforms.
- Expertise in enterprise AI platform architecture and operationalization.
- Advanced proficiency in MLOps/LLMOps frameworks and tools.
- Deep understanding of Responsible AI principles, governance, and compliance.
- Hands-on experience with cloud-based AI platforms such as AWS, Azure, or GCP.
- Technical leadership in model lifecycle management and AI observability.
- Strong knowledge of GenAI architectures, LLMs, and AI orchestration.
- Experience with scalable, secure, and production-ready AI solutions.
- Proficiency in Python and relevant AI/ML libraries such as TensorFlow, PyTorch, and scikit-learn.
- Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, or a closely related discipline.
- Certification in Data Science or Advanced Analytics from a recognized institution.
- Certification in cloud architecture or AI platform engineering.
Nice To Haves
- Experience establishing enterprise AI Centers of Excellence or platform teams.
- Knowledge of vector databases, RAG, and AI agents.
- Experience developing reusable AI architecture patterns and accelerators.
- Familiarity with business intelligence and reporting automation.
- Experience mentoring or leading cross-functional AI teams.
Responsibilities
- Lead the design and architecture of end-to-end enterprise AI platforms, ensuring scalability, reliability, and operational readiness.
- Define and implement frameworks for model lifecycle management, MLOps/LLMOps, AI observability, and operationalization.
- Establish Responsible AI principles, governance frameworks, and technical guardrails to support compliant and ethical AI deployment.
- Drive platform-level technical decision-making to enable consistent and scalable enterprise AI adoption.
- Provide architectural leadership across business, data, technology, and platform teams to translate AI strategy into production-ready solutions.
- Evaluate emerging AI technologies and assess their applicability to enterprise AI platforms.
- Guide teams in selecting models, platforms, frameworks, and architectural patterns based on business and technical requirements.
- Collaborate with senior stakeholders to define the enterprise AI roadmap and platform strategy.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
