Artificial Intelligence Engineer

Hi All,

Atain team is seeking an experienced AI Engineer with 7+ years of experience in designing, developing, and deploying enterprise-scale AI solutions. The ideal candidate will have strong expertise in Azure, Databricks, Generative AI, Agentic AI frameworks, and MCP (Model Context Protocol) Server development. This role involves building intelligent AI agents, RAG-based applications, LLM-powered solutions, and scalable MLOps pipelines to drive business innovation and operational efficiency.

Key Responsibilities

Design, develop, and deploy AI/ML and Generative AI solutions using Azure and Databricks.

Build and optimize Agentic AI systems, multi-agent workflows, and autonomous AI applications.

Develop and integrate MCP Servers for tool orchestration, context management, and external system connectivity.

Design and implement Retrieval-Augmented Generation (RAG) architectures using vector databases and enterprise data sources.

Fine-tune, evaluate, and deploy Large Language Models (LLMs) for domain-specific use cases.

Develop scalable data pipelines and feature engineering workflows using Databricks, PySpark, and Delta Lake.

Implement MLOps and LLMOps practices, including model versioning, monitoring, CI/CD, and governance.

Collaborate with business stakeholders, data engineers, architects, and product teams to translate requirements into AI solutions.

Ensure AI solutions meet security, compliance, scalability, and performance standards.

Mentor junior engineers and contribute to AI best practices and innovation initiatives.

Required Skills

AI / Generative AI

Strong experience with Large Language Models (LLMs) such as GPT, Llama, Claude, or similar.

Hands-on experience with Generative AI, Prompt Engineering, RAG, and AI Agent frameworks.

Experience building Agentic AI solutions with planning, memory, tool calling, and multi-agent orchestration.

Experience with LangChain, LangGraph, AutoGen, CrewAI, or similar frameworks.

Understanding of LLM evaluation, guardrails, and AI governance.

MCP & Agent Integration

Experience developing and integrating MCP (Model Context Protocol) Servers.

Knowledge of tool integration, context management, API orchestration, and agent communication patterns.

Experience exposing enterprise systems, APIs, and databases to AI agents through MCP architecture.

Azure & Databricks

Strong experience with Azure AI Services, Azure OpenAI, Azure ML, Azure Data Factory, Azure Functions, and Azure Storage.

Expertise in Azure Databricks, Delta Lake, Unity Catalog, MLflow, and Databricks Model Serving.

Experience building Medallion Architecture (Bronze, Silver, Gold) and Lakehouse solutions.

Strong knowledge of PySpark, Spark optimization, and distributed data processing.

Data Engineering & MLOps

Python programming with strong software engineering practices.

Experience with SQL, vector databases (FAISS, Pinecone, Chroma, Azure AI Search, Milvus), and API development.

Knowledge of MLflow, CI/CD pipelines, Docker, GitHub Actions, Azure DevOps, or similar tools.

Experience implementing monitoring, observability, and model lifecycle management.

Preferred Qualifications

Experience with healthcare, financial services, insurance, retail, aviation, or enterprise analytics domains.

Experience with fine-tuning LLMs and open-source models.

Exposure to cloud platforms such as AWS or GCP.

Azure, Databricks, or AI-related certifications preferred.

Experience leading AI projects and mentoring engineering teams.

Education

Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field.

Nice to Have

Experience with Voice AI, Conversational AI, or AI-powered automation.

Knowledge of Knowledge Graphs, Graph RAG, or advanced retrieval techniques.

Experience with enterprise-scale AI governance and responsible AI practices.

Only Immediate joiner shares their profiles on [email protected]