SDE - III, LLM

Qure.ai; Bengaluru; On-site; INR 1,500,000 - 3,500,000; Full time

Job summary

Qure.ai is seeking an LLM Engineer to accelerate its generative AI roadmap by building scalable, production-grade systems utilizing large language models across healthcare workflows. You will own the end-to-end application of LLMs—from internal tools and APIs to robust performance, usability, and safety in real-world deployments.

You will design LLM-based features across clinician-facing assistants and automated diagnostic flows, build internal tools and utilities, and collaborate with prompt

Qualifications

• Bachelor’s degree in Computer Science, Information Technology or related field.

Responsibilities

• Design and implement LLM-based features across Qure.ai products.
• Build internal tools, APIs, and developer utilities for scalable LLM integrations.
• Collaborate with prompt engineers on modular, composable workflows.
• Evaluate model performance and behavior using human feedback and metrics.
• Optimize latency, cost, and reliability of LLM systems.

Skills

LLM architectures

Python programming

OpenAI/Anthropic integration

Cloud platforms

Prompt engineering / guardrails

API development

Cross-functional collaboration

Education

Bachelor's degree in CS/IT

Tools

LangChain

Haystack

Pydantic AI

Docker

Kubernetes

Job description

Job Summary

Location: Bangalore, India

Experience: 2-5yrs

Type: Full Time

Department: Engineering

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 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 Own & Drive

• Design and implement LLM-based features across Qures 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

• Bachelors 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.