AI & Data Quality Engineer
First seen by Alion on Aug 29, 2026.
AI & Data Quality Engineer
Required Qualification Level : Bachelors degree (Undergrad) in any engineering discipline.
Preferred Qualification Level : Masters in Computer Science or IT.
Years of Experience : 5 - 8 years.
Role Summary :
- Design and develop AI-enabled data quality solutions and tools.
- Build automated data quality, profiling, monitoring and anomaly detection capabilities.
- Develop AI/ML and Generative AI capabilities to improve data quality and engineering processes.
- Build scalable data warehouse and data engineering solutions to support AI use cases.
- Develop APIs, backend services and user interfaces for AI and data quality applications.
- Implement MLOps, CI/CD and monitoring practices for AI/ML solutions.
- Collaborate closely with business, data and technology stakeholders.
Mandatory Skills :
- Strong experience in Python, SQL and software development.
- Good understanding of AI, Machine Learning, Generative AI and LLM concepts.
- Hands-on experience with AI/ML frameworks and APIs.
- Experience building data quality, data validation, profiling or monitoring solutions.
- Strong understanding of data warehousing, data modelling and data engineering.
- Experience with cloud data platforms such as Snowflake, Databricks, Redshift or equivalent.
- Experience with AWS cloud services and cloud-based application development.
- Experience with MLOps, model deployment, monitoring and lifecycle management.
- Experience with CI/CD, Git and DevOps practices.
- Experience developing REST APIs and backend services.
- Experience with frontend technologies such as React, JavaScript or TypeScript.
- Experience with data pipelines and orchestration tools such as Airflow.
- Understanding of data governance, security and metadata management.
Good to Have Skills :
- Experience with AWS Bedrock, SageMaker or equivalent AI services.
- Experience with LLM, RAG and Agentic AI solutions.
- Experience with vector databases.
- Experience with PySpark / Spark.
- Experience with Docker and Kubernetes.
- Experience with Power BI or other BI tools.
- Retail domain experience.
Traits / Abilities :
- Strong problem-solving and analytical skills.
- Strong ability to translate business needs into technical solutions.
- Curiosity and willingness to learn emerging AI technologies.
- Strong ownership mindset towards solution delivery and production support.
- Ability to work across AI, Data Engineering and Technology teams.
- Strong focus on data quality, reliability and governance.
- Ability to work effectively in ambiguous and evolving environments.
- Effective stakeholder communication.
Skills
Artificial Intelligence, Data Quality, Machine Learning, Generative AI, SQL, Python, LLM, Data Warehousing, Data Modeling, AWS, PySpark