Director, AI Engineering & Delivery
USD 117K-206K Executive-level Full Time
Tasks
- Communicate delivery progress operational risks and technical updates
- Conduct technical feasibility assessments delivery readiness and sustainability planning
- Coordinate AI delivery planning resource management and continuity
- Develop reusable AI engineering patterns and shared services
- Drive adoption of enterprise engineering standards
- Implement AI software development lifecycle SDLC processes
- Lead enterprise AI engineering execution and delivery
- Lead, mentor, and develop engineering teams
- Manage AIOps and LLMOps operational practices
- Operationalize AI governance validation responsible AI controls and secure delivery
- Operationalize scalable AI engineering practices
- Oversee solution design development validation deployment monitoring and optimization
- Research evaluate and apply emerging AI engineering automation and observability technologies
- Support vendor evaluations and build versus buy assessments
Perks/Benefits
- N/A
Skills/Tech-stack
AI Governance | AI Risk | AI risk management | AI software | AI software development | AI software development lifecycle | AI software development lifecycle SDLC | AIOps | APIs | Agentic Workflows | Agile delivery | Automation frameworks | Backlog Management | Cloud Platforms | Data integration | Delivery practices | Dependency management | Deployment management | DevOps | Development lifecycle SDLC | Drift Detection | Engineering quality | Engineering quality practices | Enterprise Architecture | Evaluation Pipelines | Incident Management | LLM Prompt | LLM Prompt Engineering | LLMOps | Language Models | Large Language Models | Model Monitoring | Operational telemetry | Orchestration frameworks | Production Support | Prompt engineering | Quality practices | Release Management | Responsible AI | Risk Management | Runtime Observability | Secure delivery | Secure delivery practices | Software Development Lifecycle (SDLC) | Sprint execution
Education
N/A
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