LLM Engineer

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 building

  RAG 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-Agent

  AI

  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).