Qualifications

• 7+ years in engineering/machine learning, with 3+ years as a Solution Architect.
• Deep proficiency in AWS, Azure, or GCP cloud platforms.
• Expert knowledge in generative AI architecture, specifically RAG and LLM orchestration.
• Strong understanding of scalable inference frameworks like vLLM and Triton.
• Experience managing AI data pipelines and feature stores such as Pinecone or Milvus.
• Proficient in MLOps and LLMOps tools like MLflow and LangSmith.
• Hands-on experience with containerization technologies such as Docker and Kubernetes.

Responsibilities

• Design and implement scalable AI solutions using cloud services.
• Architect and optimize generative AI systems with RAG and agentic workflows.
• Oversee model serving frameworks for optimal performance and reliability.
• Manage AI data pipelines to support effective data-driven decision-making.
• Implement MLOps and LLMOps practices for model tracking and evaluation.
• Utilize Infrastructure as Code to streamline AI infrastructure deployment.
• Collaborate with teams to deliver AI solutions for B2B clients.

Benefits

• Innovative work environment focused on cutting-edge AI technologies.
• Opportunities for professional growth and continuing education.
• Collaborative team culture with cross-functional teamwork.