Associate Director, AI Application Engineering
Tasks
- Align with enterprise architecture security and cloud governance
- Architect develop deploy LLM powered applications
- Architect lakehouse streaming and batch processing patterns
- Build AI microservices and APIs
- Build and maintain knowledge graphs ontologies entity resolution pipelines
- Build data ingestion transformation and enrichment pipelines
- Champion code review test driven development observability and documentation
- Conduct technical design reviews and architecture assessments
- Define reusable AI solution patterns and reference architectures
- Design AI optimized data models and schemas
- Design agentic AI workflows
- Enforce coding standards testing practices and MLOps LLMOps pipelines
- Ensure production AI performance scalability reliability security
- Evaluate emerging AI frameworks tooling and models
- Implement data quality validation and drift detection
- Implement human-in-the-loop controls
- Integrate AI capabilities with enterprise systems
- Lead and mentor AI ML and data engineering teams
- Lead rapid prototyping and proof of concept
- Manage delivery planning estimation risk management and quality assurance
- Orchestrate tools for agent workflows
- Set LLMOps monitoring and observability for deployed models
- Translate requirements into technical designs with product and data teams
Perks/Benefits
- Company-matched student loan contribution
- Continuing education support
- Continuous learning resources
- Family-friendly benefits
- Financial wellness programs
- Flexible time off
- Health care coverage
- Referral incentive awards
- Retail discounts
- Retirement planning
Skills/Tech-stack
API Development | AWS | Agent systems | Azure | Batch Processing | CRM | Cloud Architecture | Code Reviews | Data Drift | Data Drift Detection | Data Enrichment | Data Ingestion | Data Ingestion Pipelines | Data Modeling | Data Quality | Data Transformation | Data Validation | Drift Detection | ERP | Enterprise Integration | Entity Resolution | Feature Engineering | GCP | Graph Databases | Human-in-the-loop | Ingestion pipelines | Knowledge graphs | LLMOps | Lakehouse | Language Models | Large Language Models | MLOps | Machine Learning | Machine Learning Engineering | Microservices | Multi-Agent | Multi-Agent Systems | Observability | Ontology Modeling | Performance Engineering | Real Time | Real-time Streaming | Relational databases | Reliability Engineering | Retrieval-Augmented Generation | Scalability | Security Engineering | Semantic Search | Test-Driven | Test-Driven Development | The Loop | Tool orchestration | Vector Databases | Vector embeddings
Education
N/A
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