Director, AI Engineering & Agentic Platform
USD 180K-190K Executive-level Full Time
Tasks
- Build LLM-powered applications
- Build LLMOps MLOps delivery pipelines
- Build evaluation and testing frameworks
- Build scalable APIs and reusable design patterns
- Connect AI services with Snowflake and Databricks
- Create model and artifact registries
- Create vector search and retrieval services
- Design production AI platforms
- Design responsible AI governance controls
- Develop RAG pipelines
- Drive FinOps for AI workloads
- Enforce access control and entitlements
- Establish model serving and inference layers
- Evaluate and integrate third-party AI tools
- Implement CI CD for AI systems
- Implement agentic multi step workflows
- Implement auditability and traceability
- Implement monitoring for quality hallucinations and reliability
- Integrate data platforms for AI access
- Integrate security compliance and risk into deployments
- Lead and mentor AI/ML engineers
- Lead production readiness and operational support
- Manage prompt lifecycle and versioning
- Optimize latency throughput and scalability
- Set up cost observability and optimization
- Support data lineage and governance
Perks/Benefits
- N/A
Skills/Tech-stack
AI system architecture | APIs | Access Control | Artifact Registries | Auditability | CI/CD | Compliance | Data Lineage | Data Security | Databricks | Evaluation Frameworks | FinOps | Governance | Inference Optimization | Knowledge graph | LLMOps | Lifecycle Management | MLOps | Microservices | Model Serving | Model registries | Monitoring and Alerting | Privacy | Prompt engineering | Prompt lifecycle | Prompt lifecycle management | Retrieval-Augmented Generation | Semantic layer | Snowflake | System Architecture | Traceability | Vector Search
Education
N/A
Regions
Countries
States
Cities
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