Senior Data AI Engineer

Devsinc is seeking an experienced Senior Data AI Engineer to lead the development and implementation of AI-driven data solutions. In this role, you will work at the intersection of data engineering and artificial intelligence, building scalable data pipelines and machine learning models to extract actionable insights and automate decision-making processes. You will collaborate closely with data scientists, engineers, and business stakeholders to deliver innovative AI-powered solutions that drive business growth.

Key Responsibilities:

• Design, develop, and maintain scalable and robust data pipelines to support AI and machine learning workloads.
• Develop, deploy, and optimize machine learning models and AI algorithms in production environments.
• Collaborate with data scientists to understand modeling requirements and translate them into efficient data processing workflows.
• Implement data preprocessing, feature engineering, and data validation techniques to improve model accuracy and reliability.
• Utilize cloud platforms and big data technologies to manage large-scale AI projects.
• Ensure data quality, security, and compliance throughout the AI data lifecycle.
• Evaluate emerging AI technologies and tools, recommending their adoption where appropriate to enhance capabilities.
• Mentor junior engineers and provide technical leadership within the data AI team.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Data Science, AI, or related fields.
• 3+ years of experience in data engineering with a strong focus on AI and machine learning implementations.
• Proficient in programming languages such as Python, Java, or Scala with experience in ML libraries like TensorFlow, PyTorch, or scikit-learn.
• Experience building and managing data pipelines using ETL tools and orchestration frameworks (e.g., Apache Airflow).
• Strong understanding of machine learning algorithms, data preprocessing, feature engineering, and model deployment.
• Hands-on experience with cloud platforms (AWS, Azure, GCP) and AI services.
• Familiarity with big data ecosystems including Spark, Kafka, Hadoop.
• Knowledge of data storage technologies like SQL/NoSQL databases and data warehousing (Snowflake, Redshift, BigQuery).
• Strong analytical and problem-solving skills with a proactive approach to innovation.
• Excellent communication and teamwork skills to collaborate across multidisciplinary teams.
• Experience mentoring and leading junior team members is a plus.