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Lead I - Data Science (AI ML Engineer)

Actively Reviewing the Applications

UST

India, Kerala, Trivandrum Full-Time On-site
Posted 1 hour ago • Apply by May 7, 2026

Job Description

Role Description

We are seeking a highly skilled AI/ML Engineer with hands-on experience in building advanced AI systems using modern agentic frameworks, vector-based search, and cloud-native architectures. The ideal candidate will have strong engineering fundamentals, deep understanding of AI pipelines, and expertise in deploying scalable solutions on Azure.

Key Responsibilities

  • Design, develop, and optimize AI/ML solutions leveraging agentic architectures and automated workflows.
  • Implement vector-based retrieval systems, embedding pipelines, and context engineering for AI applications.
  • Build and maintain prompt engineering frameworks and LLM-driven automation workflows.
  • Develop high-performance services using Python, Java, or Go.
  • Deploy and manage cloud-native AI services on Azure, ensuring reliability, scalability, and cost efficiency.
  • Integrate with various databases and storage systems including Azure AI Search, Redis, and Cosmos DB.
  • Architect and implement serverless and containerized solutions using Azure Functions and Azure Container Apps.
  • Collaborate cross-functionally with product, cloud, and data engineering teams to deliver end‑to‑end AI features.

Required Skills & Experience

  • Hands-on experience with Agentic Layer A2A frameworks and MCP Protocol.
  • Expertise in AI/ML engineering, including:
    • Vector embeddings
    • Prompt engineering
    • Context engineering
  • Programming proficiency in any of the following:
    • Python
    • Java
  • Strong Azure Cloud experience, including:
    • Deploying AI workloads
    • Monitoring and operationalizing cloud services
  • Experience with:
    • Azure AI Search
    • Redis
    • Cosmos DB
    • (Bonus: Blob Storage, Iceberg)
  • Proven ability to design, deploy, and manage:
    • Azure Functions
    • Azure Container Apps
  • Solid understanding of:
    • Cloud‑native architecture
    • Scalability principles
    • Performance optimization
Skills

Artificial intelligence, Machine Learning, Azure, AI ML engineering, Python, Java, Agentic layer A2A framework

Required Skills

Machine Learning Engineering Automation Workflows Automation Monitoring Python Redis Azure Azure Functions Data Engineering Artificial Intelligence Cloud services Iceberg Performance optimization Azure Cloud Blob Storage systems Vector MCP Embedding Framework Prompt engineering Retrieval Java Storage Container AI/ML LLM Blob storage Serverless Advanced AI Scalability principles Embeddings
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