Data & AI Engineer

As a Data & AI Engineer, you will design, build, and optimize data pipelines, machine learning models, and AI-enabled solutions that empower enterprise teams to make smarter decisions and automate complex workflows. You will play a key role in delivering agentic capabilities by developing intelligent applications, autonomous agents, and advanced automation. You will collaborate with business and technical teams to create reliable, scalable, and secure data and AI solutions that integrate seamlessly with enterprise platforms., * Design and build scalable data pipelines to collect, clean, and organize data from various sources using modern tools.

• Integrate data and AI solutions with business applications and enterprise platforms.
• Develop and deploy machine learning models, for enterprise use cases.
• Strong knowledge of data architecture, data engineering, data modeling, data warehousing, and data platforms.
• Ensure data quality, security, and compliance across all data and AI projects, following best practices and governance frameworks.
• Create intelligent applications such as chatbots and automation tools integrated with enterprise platforms.
• Collaborate with cross-functional teams to deliver end-to-end solutions.
• Document processes and share technical knowledge to support team learning and project continuity.
• Apply advanced data engineering and machine learning techniques to solve complex business problems and optimize data architectures.
• Contribute to agentic AI initiatives, such as autonomous agents, advanced chatbots, and AI-driven automation platforms.

• Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field, or equivalent practical experience.
• Minimum 3 years of hands-on experience in data engineering, machine learning engineering, or AI solution development.
• Proficiency in SQL for data querying, transformation, and analysis.
• Strong programming skills in Python for data processing, automation, and model development.
• Experience building and maintaining data pipelines using modern tools (e.g., dbt, Fivetran, Airflow).
• Experience with cloud data platforms such as Snowflake, Databricks, BigQuery, Redshift, or Synapse.
• Experience with at least one major cloud provider (AWS, GCP, or Azure).
• Practical experience working with machine learning concepts, including model training, evaluation, and deployment.
• Exposure to MLOps practices such as model packaging, CI/CD, and monitoring.
• Experience integrating data and AI solutions with business applications or enterprise platforms.
• Experience with API integration for connecting data, AI models, and applications.
• Ability to develop and support intelligent applications (e.g., chatbots, automation tools).
• Knowledge of data quality assurance, security, and compliance best practices.
• Experience documenting processes and sharing technical knowledge with team members.
• Strong problem-solving skills and ability to work collaboratively in cross-functional teams.
• Effective written and verbal communication skills., * Master’s degree or higher in a relevant field.
• Advanced experience in data engineering, including building scalable, high-performance data architectures and ETL frameworks.
• Advanced experience in machine learning, including designing, training, and deploying complex models for real-world applications.
• Experience with agentic AI systems, such as autonomous agents, advanced chatbots, or AI-driven automation platforms.
• Experience implementing and maintaining data governance frameworks, including data lineage, metadata management, privacy, and compliance.
• Experience with containerization (Docker) and modern software development practices.
• Exposure to vector databases, semantic search, or feature stores.

Posted 5 Hours Ago Remote Hiring Remotely in USA 70K-144K Annually Mid level Remote Hiring Remotely in USA 70K-144K Annually Mid level Designs and optimizes scalable data pipelines, machine learning models, and AI-enabled enterprise applications. Builds agentic systems, chatbots, autonomous agents, and automation tools; integrates data and AI solutions with business platforms; and ensures data quality, security, compliance, and governance. The role requires Python, SQL, cloud data platforms, modern pipeline tools, MLOps, API integration, and collaborative delivery of reliable end-to-end solutions. The summary above was generated by AI Calix provides the cloud, software platforms, systems and services required for communications service providers to simplify their businesses, excite their subscribers and grow their value.