About Our Client:

The organization operates in the integration and automation technology industry, focusing on connecting diverse systems and data to enable organizations to operate more efficiently. It addresses challenges in enterprise data integration by providing an intelligent platform that supports the future of business operations through automation and connectivity. The company has experienced fast growth and serves a wide range of clients by delivering technology solutions that facilitate seamless data and system integration.

About the Opportunity:

The Senior Data Engineer - Agentic AI Engineering role is designed to develop and maintain scalable, secure, and observable data infrastructure that supports advanced AI systems such as large language model-based agents and multi-agent workflows. This position bridges experimental AI research and reliable enterprise applications, ensuring that AI features are delivered efficiently and securely. The role is critical in enabling continuous improvement and reliability of intelligent agents through robust data architectures.

Responsibilities:

• Architect and build scalable, secure, and observable data infrastructure for AI agents and workflows.

• Design and operate batch and real-time data pipelines supporting embeddings, retrieval-augmented generation systems, and memory frameworks.

• Develop and manage vector databases for low-latency and contextual AI data retrieval.

• Create data frameworks for training, evaluation, benchmarking, and continuous improvement of AI systems.

• Implement data governance, quality controls, lineage tracking, and compliance with security and privacy requirements.

• Collaborate with AI/ML, platform, and DevOps teams to transition AI prototypes into production-grade solutions.

• Optimize data systems for performance, scalability, reliability, and cost-efficiency across cloud platforms.

Requirements:

• Minimum 5 years' experience in building and operating large-scale data platforms.

• Proficiency in Python and SQL for scalable data solution development.

• Experience designing batch and streaming data pipelines with tools like Kafka or Kinesis.

• Familiarity with cloud data platforms and environments such as AWS, Azure, GCP, and tools like Snowflake.

• Knowledge of LLM and AI data workflows, including embeddings, retrieval systems, evaluation datasets, and vector databases.

• Experience utilizing DataOps/MLOps tools such as Airflow, dbt, and MLflow.

• Strong understanding of data quality, governance, security, including PII handling and access controls.

Pay Range and Compensation Package:

• Base compensation ranges from $138,862 to $173,578 depending on experience and location.

Note:

TalentHop is not the Employer of Record (EOR) for this role. Our purpose in this opportunity is to connect exceptional candidates with leading employers. We help job seekers worldwide discover roles that match their goals and guide them to complete their full application directly through the hiring company’s career page or ATS.

Job description