We are looking for a Mid-Level LLM Application Developer with 3–5 years of experience in software development, who is passionate about building intelligent applications using Azure OpenAI, Python, and LLM frameworks. This is a full-time role focused on designing, developing, and deploying scalable LLM-powered solutions, including chatbots, knowledge assistants, and RAG-based systems. You’ll be working closely with cross-functional teams to bring innovative AI solutions to life, leveraging the latest in generative AI and agentic technologies.
Job Description:
Responsibilities:
Design and develop LLM-powered applications using Python and Azure OpenAI services.
Extend digital products and platforms, and LLM Apps , with new capabilities
Support adoption of digital platforms and LLM Apps, by onboarding new clients
Driving automation to expedite and accelerate new client adoption
Build end-to-end Retrieval-Augmented Generation (RAG) pipelines, integrating vector databases, semantic search and other related tools.
Develop conversational agents and virtual assistants, using frameworks like LangChain or LlamaIndex.
Craft effective prompts using advanced prompt engineering and prompt design techniques.
Integrate LLMs with external tools, APIs, and business data systems.
Apply Agentic AI patterns to RAG and AI Workflows, interacting with LLMs by orchestrating various agents together
Deploy and manage applications using Azure Functions, Azure AI services, and serverless components.
Ensure performance, scalability, and reliability of AI solutions on Azure.
Collaborate across teams and participate in agile development processes.
Required Skills (Must Have):
Strong proficiency in Python programming language.
Expertise in Azure OpenAI Service, including foundation model usage, GPT Model family, and integration.
Build and deploy AI solutions leveraging Azure AI services (e.g., Cognitive Services, Azure AI Search).
Deep understanding of vector databases and hybrid search capabilities built on top of Azure AI Search
Deep experience in prompt engineering, including various prompting strategies (few-shot, chain-of-thought, etc.).
Hands-on experience and deep expertise in buildingRAG pipelines with vector databases and tool integrations.
Proven experience developing chatbots or virtual assistants using LLMs.
Proficiency in at least one LLM application framework (preferably., LangChain,).
In-depth understanding of LLM models, their capabilities, and applications.
Good understanding of LLM evaluations, and how to evaluate LLM model outputs.
Experience deploying with Azure Function Apps and broader Azure ecosystem.
Solid grasp of API integrations and data workflow design.
Solid experience building automation workflows and automation solutions for LLM Apps and Products, to support new client onboarding
Solid experience with data and content indexing pipelines to setup new “knowledge bases” for RAG and LLM solutions
Strong problem-solving skills and ability to deliver scalable, efficient code.
Excellent communication and team collaboration abilities.
Preferred Skills (Good to Have):
Good understanding of using AI Agents and Agentic AI Patterns to integrate with LLMs
Familiarity with Multi-AgentAI orchestration and agentic workflows.
Experience building cloud-native services with serverless architectures.
Understanding of NLP techniques and data transformation pipelines.
Familiarity with LLMOps concepts and AI model lifecycle.
Qualifications:
Bachelor’s degree in computer science, Computer Engineering, or a related field.
3+ years of experience in software development.
Experience with LLM applications and cloud platforms.
Strong understanding of software development methodologies (e.g., Agile).