Lead Full-Stack AI Engineer
Tasks
- Architect retrieval augmented generation and knowledge management
- Build agentic AI solutions with multi agent architectures
- Champion AI assisted software engineering best practices
- Deliver MLOps and LLMOps deployment evaluation monitoring and governance
- Design and implement enterprise AI platform capabilities
- Establish reusable engineering frameworks and patterns
- Implement scalable cloud native AI infrastructure
- Optimize production AI cost and operations
- Partner with security legal risk and business stakeholders
- Perform architecture reviews and provide technical mentorship
Perks/Benefits
- Adoption Assistance
- Annual discretionary bonus
- Hybrid work
- Leave programs
- Student loan repayment programs
Skills/Tech-stack
Agent systems | Agents | CI/CD | Cloud Native | Cloud platform | Distributed Systems | Embeddings | Generative AI | Google Cloud | Google Cloud Platform | Infrastructure as Code | Java | JavaScript | Knowledge graphs | Kubernetes | LLMOps | Language Models | Large Language Models | Logging | MLOps | Monitoring | Multi-Agent | Multi-Agent Systems | Observability | Python | RAG | Retrieval-Augmented Generation | Semantic Search | Terraform | TypeScript | “as-code”
Education
N/A
Roles
Engineer | Full Stack | Full Stack Engineer | Lead | Lead Full Stack Engineer | Stack Engineer
Regions
Countries
States
Cities
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