Gen AI Engineer (Candidates with below experience only must apply)

Generative AI Engineer

Overview

GenAI Engineer

Task and Responsibilities:

• Implement end-to-end Generative AI solutions on the Azure Cloud Platform, leveraging services such as:

  Azure OpenAI Service, Azure AI Search, Azure Cognitive Services,

Azure AI Foundry, Azure Machine Learning etc.

• Creating data pipelines to ingest, process, and prepare data for analysis and modeling using Azure services, such as

  Azure AI Document Intelligence

  ,

  Azure Databricks

  etc.
• Design and deploy

  RAG

  pipelines, incorporating structured and unstructured data to enhance LLM-based applications.
• Develop and orchestrate

  AI Agents

  and

  Autonomous Agents

  for real-time decision-making, task and automation.
• Fine-tune and optimize Small Language Models (

  SLMs

  ) for domain-specific applications with a focus on performance, cost, and inference latency.
• Integrate

  LLMs/SLMs

  into applications using frameworks such as

  LangChain

  ,

  Model Context Protocol

  (

  MCP

  ), etc.
• Collaborate with data scientists, ML engineers, and product teams to align AI capabilities with business goals.
• Lead technical discussions and create architecture blueprints, best practices, and governance models for GenAI adoption across the enterprise.
• Monitor and optimize deployed solutions for scalability, latency, security, and compliance.

Qualifications:

• Bachelor's or master's degree in computer science, Data Science, AI/ML, information technology, or a related field.
• Overall 8+ years’ combined experience in IT, 5+ years of experience in AI/ML solution engineering with at least 2+ years focused on Generative AI.
• Strong experience with LLMs and SLMs, including integration of open source models, prompt engineering, evaluation, and fine-tuning techniques.
• Proven track record using LangChain, Semantic Kernel, RAG, AI Agents, and MCP (Model Context Protocol) in production environments.
• Solid understanding and Hands-on experience with vector databases, embeddings, and Azure AI Search integration for semantic retrieval.
• Hands-on experience with tools like MLFlow, Azure Machine Learning, Azure OpenAI Service, Azure AI Search, Azure Cognitive Services, Azure AI Foundry, Azure Machine Learning etc.
• Familiarity with MLOps, CI/CD pipelines, and responsible AI practices.
• Experience deploying AI models on Azure Kubernetes Services (AKS) or Azure Container Apps.
• Understanding of security and compliance in AI deployments (e.g., data privacy, bias detection).
• Proficiency in programming languages like

  Python

  (essential).
• Excellent problem-solving, analytical, and critical thinking skills.
• Strong communication and collaboration skills to work effectively in a team environment.
• A passion for innovation and a desire to push the boundaries of what's possible with Gen AI.
• Relevant industry certifications, such as Microsoft Certified: Azure AI Engineer, Azure Solution Architect etc. is a plus.