Senior Consultant AI Architect ( Onsite )
Tasks
- Apply MLOps monitoring
- Build Retrieval Augmented Generation systems
- Conduct technical reviews and approvals
- Continuously improve AI powered applications
- Coordinate with security risk teams
- Create APIs for model serving
- Create proposal materials
- Deliver AI applications using agile methodologies
- Deploy and host foundational models
- Design scalable AI architectures
- Develop AI strategy
- Enable semantic search
- Ensure ethical AI practices and compliance
- Implement LLM architectures
- Implement vector databases
- Integrate AI systems with enterprise systems
- Lead cross-functional teams
- Mentor junior team members
- Perform fine-tuning
- Pilot AI use cases
- Present architecture designs to stakeholders
- Select AI technologies for compatibility
- Support RFI and RFP responses
- Translate stakeholder vision to AI implementation roadmap
Perks/Benefits
- Career growth opportunities
- Health and wellness programs
- Hybrid work environment
- Ongoing learning and development programs
Skills/Tech-stack
API Development | AWS Bedrock | Amazon SageMaker | Azure Kubernetes | Azure Kubernetes Service | Azure Machine Learning | Azure OpenAI | Azure OpenAI Service | Context Embedding | DataRobot | Databricks | Dataiku | Docker | Fine Tuning | GPU Computing | Google PaLM | Google Vertex | Google Vertex AI | Kubernetes | Kubernetes Service | LLM Architecture | Langchain | MLOps | Machine Learning | OpenAI Service | PyTorch | Python | Retrieval-Augmented Generation | Semantic Search | Serverless | Snowflake | TensorFlow | Transformer | Vector Database | Vertex AI
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
Roles
AI | AI Architect | Architect | Data Scientist | Engineer | Learning Engineer | Machine Learning Engineer | Scientist
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