A Generative Artificial Intelligence Engineer develops, designs, and manages generative models and algorithms that support the generation of new content in the form of images, text, audio, and other multimedia. They utilize GPTs, GANs, VAEs, and other deep learning architectures to craft systems capable of generating data. May work with data scientists, machine learning engineers, and software developers.
Data Engineering Architect with 12+ years of experience in enterprise data engineering, ETL, data warehousing, cloud modernization and AI/ML solutions. Technical Skills Strong expertise in Informatica PowerCenter, IDMC/IICS, PL/SQL, SQL, Python and Unix/Linux, with hands-on experience designing scalable ETL/ELT pipelines across heterogeneous sources including Oracle, SQL Server, PostgreSQL, DB2, MongoDB, APIs, JSON/XML and flat files. Experienced in AWS data and analytics services including S3, Glue, RDS, Redshift and Lambda, along with Databricks, Snowflake and Apache Airflow for cloud-based data engineering, orchestration and analytics architectures. Expertise in ETL architecture, complex transformations, full/incremental/CDC loads, SCD, data modelling, performance tuning, reconciliation and data quality.
Good Understanding of following:
AI/ML capabilities covering Python, ML pipelines, MLOps, Generative AI, LLMs, RAG, embeddings, vector databases, LangChain/LangGraph and AI agents. Experience applying AI to data quality automation, anomaly detection, ETL/code generation, intelligent monitoring, RCA, data governance and enterprise data operations. Understanding of SDLC, architecture/design governance, CI/CD, Git, Agile delivery and technical leadership, with the ability to define enterprise data and AI architectures, lead solution design and mentor engineering teams.
Roles & Responsibilities:
Define end-to-end data architecture for ETL, data warehouse, lakehouse and cloud platforms. Design source-to-target mapping, complex transformations, full/incremental/CDC loads, SCD, data modelling, performance tuning, reconciliation and data quality. Lead Informatica PowerCenter/IDMC architecture, mapping design, workflows and ETL framework standards. Design scalable data pipelines using AWS S3, Glue, RDS, Redshift, Lambda, Databricks, Snowflake and Airflow. Develop and optimize PL/SQL, SQL and Python solutions for complex data processing and validation. Define data modelling, CDC, SCD, incremental loads, reconciliation and data quality frameworks. Architect AI/ML and GenAI solutions, including LLM, RAG, embeddings, vector databases and AI agents. Drive ETL modernization and cloud migration from legacy/on-prem platforms to cloud architectures. Establish performance, security, monitoring, CI/CD and data governance standards. Lead technical design reviews, provide architecture guidance, resolve complex technical issues and mentor engineering teams. Collaborate with business, data, cloud and AI teams to translate requirements into scalable, secure and cost-effective solutions.
