Senior AI Engineer
Tasks
- Architect and optimize RAG pipelines
- Design AI evaluation frameworks
- Drive prompt engineering strategy for multi turn and multi agent interactions
- Implement LLM as judge workflows and red teaming
- Lead end to end design and delivery of production LLM applications
- Lead model fine tuning and adaptation initiatives
- Mentor AI engineers through design reviews and code reviews
- Own and evolve AI infrastructure for reliability scalability observability
Perks/Benefits
- Discounted WGU tuition
- Flexible paid time off
- Flexible spending account
- Health savings account
- Medical/Dental/Vision
- Mental health support
- Paid Holidays
- Parental leave
- Retirement savings plan
- Telehealth
- Wellbeing program
Skills/Tech-stack
AWS | Agent systems | Agentic AI | Autogen | CI/CD | CrewAI | Databricks | Embeddings | Fine Tuning | Hugging Face | Information Retrieval | LLM Evaluation | LLM-as-judge | Langchain | Language Models | Large Language Models | Llamaindex | LoRA | Model Fine-tuning | Multi-Agent | Multi-Agent Systems | Observability | Ollama | PEFT | Prompt engineering | Python | RAG | RLHF | Red Teaming | Reliability | Retrieval-Augmented Generation | Scalability | System design | Test automation | VLLM | Vector Databases
Education
N/A
Roles
Regions
Countries
States
Cities
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