GenAI & Databricks- R
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Job Location:
Monthly Salary:
Posted on:
13-10-2025
Vacancies:
1 Vacancy
Job Summary
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.
- 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.
Mandates
We may use artificial intelligence (AI) tools to support parts of the hiring process such as reviewing applications analyzing resumes or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed please contact us.
About Company
Brillio is a global leader in Enterprise Digital Transformation Solutions, providing strategic consulting services and solutions using emerging technologies.
