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Tech Stack
Tools & technologiesAWSAzureCloudGoogle Cloud PlatformPython
About the role
Key responsibilities & impact- Drive the design, development, and operationalization of advanced large-language-model capabilities across a cloud-based analytics ecosystem
- Lead innovation efforts around AI, including architecture and strategy for fine-tuning, retrieval-augmented generation (RAG), agentic frameworks, and domain-specific model adaptation
- Guide development of high-impact prototypes
- Oversee the evolution of scalable LLM pipelines
- Ensure governance, security, and performance across model implementations
- Partner with engineering, product, and data teams
- Provide technical leadership and evaluate emerging LLM technologies
- Set best practices and help drive practical, safe, and effective deployment of generative AI
Requirements
What you’ll need- 5 years with BS/BA; 3 years with MS/MA; 0 years with PhD; 9 years with a high school diploma
- Deep expertise in LLM architectures, transformer models, and modern generative AI techniques
- Demonstrated experience leading fine-tuning efforts, parameter-efficient training (e.g., LoRA/PEFT), and advanced prompt engineering
- Proven ability to design and implement end-to-end RAG pipelines, including embedding workflows, retrieval optimization, and vector database integrations
- Hands-on experience with LLM frameworks or orchestration toolchains such as LangChain or LlamaIndex
- Strong Python development skills and experience with distributed compute or GPU-accelerated training environments
- Experience architecting and deploying AI/ML or LLM workflows within Azure, AWS, or GCP
- Understanding of MLOps/LLMOps practices, including versioning, CI/CD, automated testing, monitoring, and model governance
- Ability to lead technical discussions, mentor team members, and communicate complex AI concepts to diverse audiences
- US Citizen with the ability to obtain/maintain a Public Trust clearance
Benefits
Comp & perks- Potential eligibility for overtime
- Potential eligibility for shift differential
- Potential eligibility for a discretionary bonus