AI & Data Quality Engineer

Position: AI & Data Quality Engineer

Required Qualification Level: Bachelors degree (Undergrad) Qualification Field: Any engineering discipline

Preferred Qualification Level: Masters Qualification Field: Computer Science or IT

No. Position: 1

Location: Bangalore

Years of Experience: 58 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.

Compensation: 2,100,[hidden],500,000.00 per year

Work Location: In person .