Agentic AI- AI​/ML Engineer

Agentic AI- AI/ML Engineer

Role:
Remote

Primary Responsibilities:

• AI/ML Development and Deployment:
  • Architect and implement scalable ML solutions using Azure ML Studio and Azure Machine Learning services
  • Fine-tune and deploy LLMs for enterprise-grade applications
  • Design and build RAG pipelines leveraging Azure services and vector databases
  • Develop and orchestrate multi-agent LLM systems for complex workflows
  • Ensure robust model deployment, monitoring, and performance optimization in production environments
• Azure Platform Engineering:
  • Leverage Azure services such as Azure Data Lake, Azure Synapse, Azure Blob Storage, and Azure Cognitive Search for data ingestion and processing
  • Integrate AI models with Azure-based data pipelines and APIs
  • Use Azure Dev Ops for CI/CD of ML workflows and model versioning
  • Apply MLOps best practices for model governance, monitoring, and retraining
  • Ensure compliance with data governance, privacy, and security standards in cloud environments
• Data Engineering and Processing:
  • Build and maintain ETL/ELT pipelines for structured and unstructured data using Databricks and Apache Spark
  • Prepare and transform structured and unstructured data using Python, PySpark, and SQL for training and inference
• Collaboration and
  
  Innovation:
  • Collaborate with data scientists, product managers, and engineers to deliver AI-driven features
  • Stay current with advancements in generative AI, LLMs, and Azure AI services
  • Contribute to the continuous improvement of AI/ML pipelines and best practices

Required Qualifications:

• Experience:
  • 5+ years of hands-on experience in AI/ML engineering with a focus on Azure
  • Proven experience in deploying ML models using Azure ML Studio and Azure Machine Learning
  • Experience working with LLMs, RAG systems, and AI agents
• Technical
  
  Skills:
  • Experience with Databricks, Apache Spark, and Azure Data services
  • Familiarity with MCP, Langchain, vector databases and embedding models
  • Knowledge of Azure Dev Ops and CI/CD for ML workflows
  • Proficiency in Python, SQL, LLMs and Py Spark
• Soft Skills:
  • Proven solid analytical and problem-solving skills
  • Proven effective communication and collaboration with cross-functional teams
  • Demonstrated ability to translate business requirements into technical solutions