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AI Engineer

ZensarBengaluru🇮🇳India

Quick overview

SeniorityMid Senior
Work modeHybrid
LocationBengaluru, India
Stakeholder ManagementDockerMicroservicesMongoDBSQLScalaAWSMLOpsMLflowNLPScikit-learnScrumComplianceDeep LearningHugging FaceJavaLLMPyTorchPythonTensorFlowGenerative AIAzurePostgreSQLKubernetesJavaScriptMachine LearningSQL ServerAgileData AnalysisPrompt EngineeringCI/CDLangChainRAG

Job description

Key Responsibilities

AI & Machine Learning Development

  • Design, develop, and deploy AI/ML models for business use cases.
  • Build and optimize machine learning pipelines from data preparation to model deployment.
  • Develop predictive, classification, recommendation, and NLP solutions.
  • Fine-tune and evaluate foundation models and LLMs.

Generative AI Solutions

  • Design and implement Generative AI applications using LLMs.
  • Develop Retrieval-Augmented Generation (RAG) solutions.
  • Create prompt engineering frameworks and reusable AI workflows.
  • Integrate AI copilots, chatbots, and virtual assistants into enterprise platforms.
  • Implement AI governance, monitoring, and responsible AI practices.

Data Engineering & Integration

  • Collaborate with Data Engineers and Data Scientists to prepare training datasets.
  • Develop APIs and microservices for AI model consumption.
  • Integrate AI services with enterprise systems and cloud platforms.

Model Deployment & Monitoring

  • Deploy AI solutions using MLOps best practices.
  • Monitor model performance, accuracy, drift, and reliability.
  • Ensure scalability, security, and compliance requirements are met.

Required Technical Skills

AI / ML Technologies

  • Machine Learning Algorithms
  • Deep Learning
  • Natural Language Processing (NLP)
  • Generative AI
  • Large Language Models (LLMs)
  • Prompt Engineering
  • Vector Databases

Programming Languages

  • Python (Mandatory)
  • SQL
  • Optional: Java, JavaScript, or Scala

AI Frameworks & Libraries

  • TensorFlow
  • PyTorch
  • Scikit-learn
  • LangChain
  • LlamaIndex
  • Hugging Face Transformers
  • OpenAI APIs / Azure OpenAI

Vector Databases

  • Pinecone
  • Weaviate
  • ChromaDB
  • FAISS

Cloud & MLOps

  • Azure AI Services / Azure OpenAI
  • AWS Bedrock / SageMaker
  • Google Vertex AI
  • MLflow
  • Docker
  • Kubernetes
  • CI/CD Pipelines

Database Technologies

  • SQL Server
  • PostgreSQL
  • MongoDB
  • Cosmos DB

Leadership & Soft Skills

  • Strong analytical and problem-solving skills.
  • Excellent communication and stakeholder management.
  • Ability to translate business problems into AI-driven solutions.
  • Experience working in Agile/Scrum environments.
  • Strong collaboration with cross-functional teams.

Preferred Qualifications

  • Experience building enterprise AI assistants and chatbots.
  • Hands-on experience with RAG architectures and vector search.
  • Knowledge of Responsible AI, AI Safety, and AI Governance.
  • Exposure to Agentic AI frameworks and autonomous AI workflows.
  • Experience with Retail, E-commerce, BFSI, Healthcare, or Supply Chain domains.

Educational Qualification

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

Preferred Certifications

  • Microsoft Azure AI Engineer Associate (AI-102)
  • Microsoft Azure Data Scientist Associate (DP-100)
  • AWS Machine Learning Specialty
  • Google Professional Machine Learning Engineer
  • TensorFlow Developer Certificate

Key Competencies

  • Artificial Intelligence
  • Generative AI
  • Machine Learning
  • Prompt Engineering
  • LLM Development
  • NLP
  • RAG Architecture
  • MLOps
  • Data Analytics
  • Innovation & Problem Solving

Required Technical Skills

AI / ML Technologies

  • Machine Learning Algorithms
  • Deep Learning
  • Natural Language Processing (NLP)
  • Generative AI
  • Large Language Models (LLMs)
  • Prompt Engineering
  • Vector Databases

Programming Languages

  • Python (Mandatory)
  • SQL
  • Optional: Java, JavaScript, or Scala

AI Frameworks & Libraries

  • TensorFlow
  • PyTorch
  • Scikit-learn
  • LangChain
  • LlamaIndex
  • Hugging Face Transformers
  • OpenAI APIs / Azure OpenAI

Vector Databases

  • Pinecone
  • Weaviate
  • ChromaDB
  • FAISS

Cloud & MLOps

  • Azure AI Services / Azure OpenAI
  • AWS Bedrock / SageMaker
  • Google Vertex AI
  • MLflow
  • Docker
  • Kubernetes
  • CI/CD Pipelines

Database Technologies

  • SQL Server
  • PostgreSQL
  • MongoDB
  • Cosmos DB

Leadership & Soft Skills

  • Strong analytical and problem-solving skills.
  • Excellent communication and stakeholder management.
  • Ability to translate business problems into AI-driven solutions.
  • Experience working in Agile/Scrum environments.
  • Strong collaboration with cross-functional teams.

Preferred Qualifications

  • Experience building enterprise AI assistants and chatbots.
  • Hands-on experience with RAG architectures and vector search.
  • Knowledge of Responsible AI, AI Safety, and AI Governance.
  • Exposure to Agentic AI frameworks and autonomous AI workflows.
  • Experience with Retail, E-commerce, BFSI, Healthcare, or Supply Chain domains.

Educational Qualification

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

Preferred Certifications

  • Microsoft Azure AI Engineer Associate (AI-102)
  • Microsoft Azure Data Scientist Associate (DP-100)
  • AWS Machine Learning Specialty
  • Google Professional Machine Learning Engineer
  • TensorFlow Developer Certificate

Key Competencies

  • Artificial Intelligence
  • Generative AI
  • Machine Learning
  • Prompt Engineering
  • LLM Development
  • NLP
  • RAG Architecture
  • MLOps
  • Data Analytics
  • Innovation & Problem Solving
ApplyOr apply on Zensar's site