Sr. AI Engineer (Applied AI & ML Systems)
Tasks
- Build LLM-based applications
- Create multi step agentic workflows
- Define AI evaluation strategies
- Design AI solutions for business problems
- Enable observability and alerting in production
- Implement Retrieval-Augmented Generation (RAG)
- Integrate AI into enterprise systems
- Monitor and troubleshoot production AI systems
- Optimize quality latency cost reliability maintainability
- Set up experimentation and versioning
Perks/Benefits
- E learning license
- Hackathons
- Healthcare benefits
- Home office setup allowance
- Identity theft protection
- Legal assistance
- Life and disability coverage
- Paid time off
- Pet insurance
- Remote work flexibility
- Retirement plan contributions
- Tuition reimbursement
- Volunteer time off
Skills/Tech-stack
Agentic AI | Context engineering | Continuous Improvement | Data Engineering | Data Pipelines | Evaluation Frameworks | Experimentation | Fine Tuning | Human-in-the-loop | LLM Fine-tuning | Language Models | Large Language Models | Machine Learning | Observability | Prompt engineering | Python | Retrieval-Augmented Generation | The Loop | Vector Databases | Version control
Education
Roles
AI | AI Engineer | Engineer | Learning Engineer | Machine Learning Engineer
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