LLM Engineer

Key Responsibilities: - Design and implement LLM-based features across Qure's products, including clinician-facing assistants and automated diagnostic flows. - Build internal tools, APIs, and developer-facing utilities to enable scalable LLM integrations. - Collaborate with prompt engineers to design modular, composable workflows (e.g., RAG, chaining, structured prompting). - Evaluate model performance and behavior across tasks using human feedback and automated metrics. - Optimize latency, cost, and reliability of LLM systems using caching, batching, and fallback strategies. - Deploy and monitor LLM services in production, integrating observability and usage analytics. - Build systems for prompt versioning, LLM configurations, and multi-model experimentation. - Lead cross-functional initiatives and drive end-to-end project execution across engineering, product, and clinical teams. - Contribute to internal LLM guidelines, safety practices, and developer enablement. - Foster a culture of collaboration, ownership, and technical excellence in building impactful LLM-driven solutions. Required Skills & Qualifications: - Bachelor's degree in Computer Science, Information Technology, or a related field. - Solid understanding of LLM architectures, inference workflows, context management, and prompt patterns. - Strong programming skills in Python; familiarity with frameworks like LangChain, Haystack, or Pydantic AI. - Experience integrating OpenAI, Anthropic, or open-source models into production systems. - Familiarity with emerging LLM protocols (e.g., MCP) and frameworks enabling agentic behaviors (autonomous agents, task decomposition, memory systems). - Proven ability to work across infrastructure, product, and research teams. - Comfort with cloud platforms (AWS/GCP), containerized deployments (Docker/K8s), and observability tools. - Strong understanding of LLM guardrails to ensure responsible, safe, and reliable production usage. - Strong problem-solving, communication, and cross-functional collaboration skills. Preferred Skills: - Experience in the healthcare industry, with understanding of compliance and security requirements. - Experience building user-facing tools or assistants powered by LLMs. - Strong sense of ownership and ability to balance experimentation with production readiness. - Familiarity with agile methodologies and project management practices. Skills: Machine Learning, Nlp, Tensorflow, Pytorch, Sql, Data Analysis, Python Experience: 0.00-3.00 Years