Senior Artificial Intelligence Engineer

4 - 7 years

8 - 18 Lacs

Posted:1 day ago| Platform: Naukri logo

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Work Mode

Remote

Job Type

Full Time

Job Description

Role Overview:

Senior AI Engineer

This is a hands-on leadership role,not a people-management-only position. You will write code, ship models, and raise the technical bar of the AI team while collaborating closely with product and engineering leadership.

What You Will Do:

Lead Core AI Systems

  • Architect and build AI systems for:
    • Automated exam evaluation (objective and subjective answers)
    • Rubric-based scoring, normalization, and consistency checks
    • NLP-based answer understanding, similarity scoring, and feedback generation
  • Design scalable, reliable AI pipelines from data ingestion to inference and monitoring.
  • Evaluate, fine-tune, and deploy modern NLP models and LLMs for education use cases.

Own AI Quality, Performance & Scale:

  • Set standards for model evaluation, testing, and production readiness.
  • Balance trade-offs between accuracy, latency, cost, and explainability.
  • Implement monitoring, alerting,and retraining strategies for production models.
  • Address model drift, bias, and edge cases in high-stakes evaluation systems.

Drive Execution & Mentorship:

  • Take ownership of high-impact AI initiatives from concept to launch.
  • Mentor junior and mid-level AI engineers through code reviews and technical guidance.
  • Collaborate with product managers to translate educational and business requirements into AI solutions.
  • Partner with backend engineers to integrate AI systems into scalable services.

Innovation & Strateg:

  • Identify opportunities where AI can create competitive advantage.
  • Prototype and validate new AI-powered features and products.
  • Stay current with advancements in NLP, LLMs, and applied AI, and apply them pragmatically.

Required Qualifications :

  • Bachelors or Masters degree in

    Computer Science, AI, Data Science, or related field

    .
  • 6+ years of experience building and deploying AI/ML systems in production.
  • Strong expertise in

    Python

    and modern ML frameworks.
  • Deep understanding of

    NLP techniques

    , including transformers, embeddings, and semantic similarity.
  • Hands-on experience with

    LLMs

    , including fine-tuning, prompt engineering, and evaluation.
  • Proven experience deploying models as scalable services (APIs, microservices).
  • Strong system design and problem-solving skills.

Strongly Preferred Qualifications:

  • Experience building AI systems in

    education, assessment, or other high-stakes decision domains

    .
  • Experience with

    MLOps

    tools and practices (MLflow, Airflow, CI/CD for ML).
  • Familiarity with vector databases, retrieval-augmented generation (RAG), and ranking systems.
  • Cloud experience (AWS, GCP, or Azure).
  • Experience handling large datasets and high-throughput inference systems.
  • Strong opinions on AI quality, reliability, and engineering rigor.

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