We’re building the next generation of intelligent claims solutions—and you’ll be at the heart of it. As our
Lead LLM Engineer
, you will own the design, deployment, and optimization of our Azure-based LLM stack. From fine-tuning GPT-style models for claims quality assurance to standing up scalable inference endpoints and retrieval pipelines, you’ll bring cutting-edge ML techniques to production in a high-stakes, performance-sensitive environment.
This is a
player-coach
position—combining hands-on LLM development with strategic technical leadership. You’ll guide engineers, shape the architecture of our language-model platforms, and collaborate closely with product, data, and platform teams to deliver high-impact AI capabilities for text understanding, information extraction, and domain-specific generation.
Responsibilities
- Lead the design and deployment of large language model infrastructure using Azure ML and AKS.
- Fine-tune transformer models (e.g., GPT) using LoRA, QLoRA, and PEFT for downstream QA and classification tasks.
- Build and manage vector stores (e.g., FAISS, Pinecone) and retrieval pipelines as part of RAG architectures.
- Develop low-latency, fault-tolerant inference services with FastAPI or Flask, integrated with Azure AD and secured via Key Vault.
- Optimize model performance using quantization, distillation, and other compression techniques.
- Monitor runtime systems using Azure Monitor, Grafana, and related tooling to meet enterprise SLAs.
- Collaborate across product, engineering, and operations teams to align on model behavior, deployment strategies, and performance goals.
- Own cost visibility and optimization across Azure ML, AKS, and related infrastructure.
Required Skills
- Deep experience fine-tuning transformer models using LoRA, QLoRA, and PEFT
- Building retrieval pipelines with vector databases (FAISS, Pinecone)
- Proficient in Python and familiar with Go or Java microservices
- Containerized deployment using Docker and Kubernetes (AKS), with Azure ML and Azure Container Instances
- API development with FastAPI or Flask; Azure AD integration and secret management via Key Vault
- Experience with model optimization (quantization, distillation) and monitoring (Azure Monitor, Grafana)
Qualifications
- Bachelor’s degree in Computer Science, Data Science, or related field; Master’s preferred
- 6–10+ years of experience in AI/ML engineering, with hands-on deployment of LLMs in production
- Demonstrated success building scalable, enterprise-grade ML systems, ideally in regulated industries
- Strong track record of architectural ownership and mentoring in a high-performance team
- Effective cross-functional communicator with a focus on delivering production-ready AI solutions
Why Join RENFROE?
We believe that success starts with our people. By joining our team, you’ll become part of a culture built on strong values:
- Excellence
: We are dedicated to excellence in every aspect of our work. We seek the best minds and talents and provide them with opportunities for professional growth and continuous learning.
- Growth
: Growth is the cornerstone of our company’s mission. By driving innovation, expanding our reach, and continuously improving our services, we ensure the company’s progress and success. At the same time, we remain dedicated to supporting the personal growth of our employees, fostering a dynamic and thriving workplace for all.
- Curiosity
: We foster curiosity and innovation, encouraging creative thinking and exploration of new ideas to remain at the forefront of our industry.
- Empathy
: A supportive and understanding workplace is key to our success. We value empathy and build relationships based on trust and mutual respect.
- Integrity
: Transparency and honesty are at the core of our business practices. We uphold the highest ethical standards in all that we do.
- Service
: Service is at the heart of our values. We are committed to making a positive impact on our clients, our community, and each other.