Principal Engineer, Data Analytics Engineering

6 - 10 years

11 - 15 Lacs

Posted:6 days ago| Platform: Naukri logo

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Job Type

Full Time

Job Description

Position: Principal AI Engineer (Data Engineering & GenAI)

We are seeking a Principal AI Engineer with deep expertise in data engineering, Generative AI (GenAI), and AWS cloud platforms to architect and lead scalable AI-driven solutions that address complex business and technology challenges.

Key Responsibilities

  • AI Platform Architecture:

    Design and implement scalable AI/ML and GenAI solutions on AWS using modern data engineering frameworks and best practices.
  • Data Engineering Leadership:

    Drive the development of robust data pipelines, ETL/ELT frameworks, and data models that support AI/ML and analytics use cases at scale.
  • Generative AI Solutions:

    Lead the exploration, prototyping, and deployment of GenAI applications (LLM-based copilots, RAG pipelines, autonomous agents) across enterprise scenarios.
  • Technology Strategy:

    Evaluate and adopt emerging technologies to strengthen AI and data engineering efficiency and capabilities.
  • Cloud & Infrastructure:

    Define and implement cloud-native architectures using AWS services (S3, Glue, Redshift, EMR, Lambda, SageMaker, Bedrock, EKS).
  • Collaboration & Influence:

    Partner with data scientists, product managers, and business stakeholders to translate business needs into scalable technical solutions.
  • Best Practices & Governance:

    Establish coding standards, DevOps/MLOps practices, and enforce data governance and security controls for AI workloads.
  • Mentorship & Leadership:

    Guide and mentor engineers and data professionals, fostering innovation, technical excellence, and best practices.

Basic Qualifications

  • Bachelor s or Master s degree in

    Computer Science, Data Engineering, AI/ML

    , or related field.
  • 9+

    years of experience in

    data engineering, AI/ML systems, and cloud computing

    .
  • Proven expertise with

    AWS cloud ecosystem

    (S3, Glue, Redshift, EMR, Lambda, SageMaker, Bedrock) and

    Databricks

    .
  • Hands-on experience with

    Generative AI models

    (LLMs, diffusion models), frameworks (LangChain, Hugging Face, OpenAI/Anthropic APIs), and

    RAG

    implementations.
  • Strong programming skills in

    Python, SQL

    , and at least one compiled language (

    Java

    , Scala, or Go).
  • Experience with

    modern data engineering tools and pipelines

    (Airflow, Spark, Kafka, dbt, Snowflake).
  • Excellent problem-solving skills with experience in architecture design and stakeholder communication.

Preferred Qualifications

  • Experience with

    vector

    and

    graph

    databases (e. g. , Pinecone, Weaviate, pgvector, Neo4j).
  • Working knowledge of

    MCP

    (Model Context Protocol) for orchestrating and managing AI agent workflows.
  • Familiarity with containerization and orchestration (Docker, Kubernetes, EKS)
  • Knowledge of

    MLOps/LLMOps

    practices and

    CI/CD pipelines

    for AI workloads (e. g. , MLflow, Kubeflow, LangSmith).
  • Strong understanding of data security, compliance, and governance in cloud and AI systems.

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