SDE - III, LLM

Posted 5 Days Ago
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Bengaluru North, Yelahanka, Bengaluru Urban, Karnataka, IND
In-Office
Mid level
Healthtech
The Role
Build and deploy production-grade LLM features for healthcare workflows, including clinician assistants and diagnostic automation. Develop APIs, internal tools, RAG workflows, model integrations, prompt management, evaluation systems, observability, and safety guardrails. Optimize latency, cost, and reliability through caching, batching, and fallback strategies. Collaborate across infrastructure, product, research, and clinical teams while leading end-to-end initiatives and supporting responsible LLM adoption.
Summary Generated by Built In

Location: Bangalore, India

Experience: 2-5yrs

Type: Full Time

Department: Engineering



About Us

Qure.ai is a global healthtech company using artificial intelligence to improve disease detection and patient outcomes at scale. Our solutions are deployed across hospitals, diagnostic networks, and public health programs worldwide.

Today, our technology has impacted 40M+ lives across 105+ countries, deployed across 5,200+ sites, and powered by one of the world’s largest real-world medical imaging datasets. With 26 FDA-cleared indications, we are helping shape the future of AI-driven healthcare.


The Opportunity

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.


What You’ll Own & Drive

  • 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. 


Core Skills Required

  • 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. 



Life at Qure

  • Flexibility & Ownership
    • Hybrid work culture
    • Relocation support (where applicable)
    • Opportunity to work on global markets
  • Growth & Learning
    • Learning and development allowance
    • High ownership and accelerated career growth
  • Wellbeing
    • Comprehensive health insurance
    • Free online doctor consultations
    • Unlimited therapy sessions
    • Fitness & wellness allowance
  • Culture & Community
    • Annual and team offsites
    • Complimentary meals at the office
    • Gaming zone (yes - including a PS5)



Our Values

  • Humble: Curious, open to feedback, and focused on team success over individual credit.
  • Hungry: High ownership, relentless drive, and a constant push for better outcomes.
  • Smart: Structured thinking with empathy, solving complex problems with clarity and strong collaboration.


Skills Required

  • 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
  • Experience with LLM frameworks such as LangChain, Haystack, or Pydantic AI
  • Experience integrating OpenAI, Anthropic, or open-source models into production systems
  • Familiarity with MCP and agentic AI frameworks
  • Ability to work across infrastructure, product, and research teams
  • Experience with AWS or GCP
  • Experience with Docker and Kubernetes
  • Familiarity with observability tools
  • Understanding of LLM guardrails and responsible AI practices
  • Strong problem-solving, communication, and cross-functional collaboration skills
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The Company
HQ: New York, NY
277 Employees
Year Founded: 2016

What We Do

From medical images to connected devices, the amount of medical data being generated is growing exponentially. This coupled with new forms of data such as the ones generated by genome sequencing and biosensors renders traditional diagnostic methods obsolete. At Qure, we are a team of passionate computer scientists, medical practitioners and bioinformaticians who are on a mission to make healthcare more accessible and affordable using the power of deep learning. We believe that Artificial Intelligence (AI) is the key in ensuring that healthcare practitioners can focus on cases that truly matter, letting machines diagnose or treat the easier ones. Our aim is to leverage deep learning effectively to diagnose disease from radiology and pathology imaging, and create personalized cancer treatment plans from psychopathology imaging and genome sequences. Our research is done in collaboration with several hospital chains, universities and research institutions. If you are a medical institution and would like to collaborate with us, please reach out to us.

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