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GenAI & Databricks- R01556764

2 weeks ago

Bengaluru, Karnataka, India Brillio LLC Full time ₹ 20,00,000 - ₹ 25,00,000 per year
GenAI & Databricks- R

Data Scientist

Primary Skills
  • Data Science skill - Machine Learning, NLP, and LLMs
  • Databricks

Experience- 5 to 8yrs

Specialization
  • Data Science Advanced: Generative AI & Databricks
Job requirements
  • Job Title: Senior AI Engineer – Generative AI & Databricks
  • Experience: 5-8+ Years
  • About the Role
  • We are seeking a Senior AI Engineer with strong expertise in Generative AI (GenAI), Databricks, and end-to-end ML/LLM systems.
  • You will be responsible for designing, building, and deploying intelligent, scalable GenAI solutions integrated into enterprise-grade data and analytics platforms.
  • The ideal candidate combines strong software engineering, MLOps, and LLM engineering experience — with the ability to lead AI agentic workflows, data pipeline optimization, and model-driven automation using Databricks, MLflow, and Azure/Snowflake ecosystems.
  • Key Responsibilities
  • 1. Solution Architecture & Implementation
  • Design and implement end-to-end Generative AI solutions on Databricks, leveraging Unity Catalog, MLflow, Delta Lake, and Vector Search.
  • Architect LLM-based multi-agent frameworks for intelligent automation, chatbot systems, and document reasoning tasks.
  • Integrate Cortex AI, OpenAI, or Anthropic APIs for retrieval-augmented generation (RAG), conversational reasoning, and workflow orchestration.
  • 2. Model Development & Optimization
  • Fine-tune and evaluate LLMs and domain-specific NLP models (NER, Risk Assessment, Question Answering).
  • Develop pipelines for prompt engineering, context management, model evaluation, and hallucination detection.
  • Optimize inference performance, latency, and cost across multi-cloud and Databricks environments.
  • 3. Data Engineering & Governance
  • Collaborate with data engineering teams to ensure clean, well-governed, and vectorized data pipelines.
  • Build and maintain feature stores and embeddings stores using Databricks or Snowflake.
  • Implement data validation, lineage, and monitoring using Delta Live Tables and Unity Catalog.
  • 4. MLOps & Automation
  • Build reusable ML pipelines using Databricks Repos, MLflow, and Feature Store.
  • Automate deployment, monitoring, and retraining workflows for continuous model improvement.
  • 5. Collaboration & Leadership
  • Partner with product managers, data scientists, and business stakeholders to translate ideas into production-ready AI systems.
  • Review code, mentor junior engineers, and enforce best practices in scalable AI/ML development.
  • Contribute to internal knowledge bases, documentation, and reusable component libraries.
  • Required Skills & Expertise
  • Core AI/ML
  • Strong background in Machine Learning, NLP, and LLMs (Transformers, RAG, embedding models).
  • Proven experience fine-tuning or implementing models using Hugging Face, LangChain, LlamaIndex, or OpenAI API.
  • Knowledge of retrieval-augmented generation, multi-agent orchestration, and context management.
  • Databricks & Cloud Ecosystem
  • Expertise in Databricks (Delta Lake, MLflow, Unity Catalog, Feature Store, Vector Search).
  • Familiarity with Azure Databricks, Azure OpenAI, or Snowflake Cortex AI.
  • Experience integrating external APIs and cloud-native microservices (FastAPI, REST, or gRPC).
  • Programming & Engineering
  • Strong proficiency in Python, SQL, PySpark, and Databricks Notebooks.
  • Experience building modular codebases, deploying APIs, and working with CI/CD pipelines (GitHub Actions, Azure DevOps).
  • Hands-on experience with Streamlit, Gradio, or other UI frameworks for AI app development.
  • MLOps & Validation
  • Hands-on with MLflow tracking, model registry, and experiment management.
  • Experience in AI validation, faithfulness scoring, drift detection, and integrity match metrics.
  • Working knowledge of Docker, Kubernetes, and inference scaling techniques.
  • Soft Skills
  • Strong communication, stakeholder management, and ability to translate business problems into AI solutions.
  • Comfort working in agile, multi-disciplinary environments.
  • Passion for innovation, experimentation, and applied AI problem-solving.

Mandates

  • • Need GenAI Data Scientist – Databricks certified ML Engineer and work closely with customers.
    • Use case will involve data extract from pdf-based documents.
    • Leverage Databricks native solutions.