LLM Engineer

About Qure.AI:

Qure.AI is an applied healthcare AI company solving high stakes problems in global healthcare. With 18 FDA and 62 CE marking clearances to date, we create innovative solutions that significantly improve patient outcomes across various care domains, including lung cancer, tuberculosis, and stroke, impacting ~15 million patients annually in over 100 countries. Our teams are empowered by a strong infrastructure, state-of-the-art tools, and resources, enabling them to tackle real-world problems efficiently. Each contribution you make becomes part of a global diagnostic network, influencing the lives of over 32 million people. At Qure AI, we are dedicated to cultivating a diverse and inclusive environment and take pride in being an equal-opportunity employer.

About the job

Job Title: LLM Engineer

Department: Engineering

Location: Bangalore

Years of Experience: 2-5 years

Employment Type: Full-time, Permanent

Key Relationships: Director - Engineering

We are looking for an LLM Engineer to accelerate our generative AI roadmap by building scalable, production-grade systems that leverage large language models across healthcare workflows. This role goes beyond prompt design, you’ll own the end-to-end application of LLMs, from architecting internal tools and APIs to ensuring robust performance, usability, and compliance in real-world deployments. If youre passionate about building the foundational tech to make LLMs work reliably in critical settings, we want to talk to you.

Key Responsibilities

• Design and implement LLM-based features across Qure’s products, from clinician-facing assistants to 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 both 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 to manage 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 and 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 such as MCP and frameworks that enable agentic behaviours (e.g., autonomous agents, task decomposition, memory systems)
• Proven ability to work across infra, product, and research teams.
• Comfort with cloud platforms (AWS/GCP), containerized deployments (Docker/K8s), and observability tools.
• Solid understanding of how to set up guardrails around LLMs to ensure responsible, safe, and reliable usage in production systems.
• Strong problem-solving, communication, and cross-functional collaboration skills.

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Preferred Skills

• Experience in the healthcare industry, with an 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.