About this role:

In this role, you will:

• Design and build scalable, production-grade data pipelinesthat reliably move and transform data between on-premise systems and public cloud environments, keeping the platform's AI-ready data stores fresh, complete, and trustworthy.

• Build Gen AI and agentic solutionsthat automate data curation, enrichment, and analysis — using AI agents to accelerate data quality checks, anomaly detection, and insight generation across the platform.

• Own data quality and analytics capabilities end to end— designing validation frameworks, monitoring, profiling, and analytics tooling that give the platform and its consumers confidence in the data.

• Build production-grade data and ML pipelines in Python, leveraging modern ML and Gen AI frameworks for data transformation, enrichment, and agentic analytics at scale.

• Own technical design across the ingestion-to-retrieval lifecycle— from on-prem and cloud ingestion through transformation, storage, and the gateway that serves governed, AI-ready data to downstream model applications.

• Establish engineering rigor for the platform's data and AI-driven components— evaluation harnesses, data quality checks, drift monitoring, and reproducibility for pipelines and agentic analytics workflows.

• Collaborate closely with data engineers, platform engineers, and applied AI engineersto ensure new pipeline, data quality, and agentic analytics capabilities integrate cleanly with the broader enterprise-grade data platform architecture.

• Partner with the modeling and applied AI teamsto ensure the data pipelines, quality signals, and agentic analytics you build translate directly into better agent performance in production.

• Mentor engineers on the teamin Gen AI and agentic solution design, scalable data pipeline engineering, and data quality and analytics best practices.

• Contribute to architectural decisions and technical reviews, representing the data platform's pipeline, data quality, and agentic analytics capabilities in cross-team and leadership forums.

Required Qualifications:

• 7+ years of Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education

• 2+ years of experience building Gen AI and agentic solutions.

• 3+ years of experience building scalable, production-grade data pipelines and data quality analysis.

• 5+ years of experience with Python, with experience in ML frameworks.

Desired Qualifications:

• Experience building or operating enterprise-grade, AI-ready data platforms in regulated industries (financial services, healthcare, or comparable).

• Hands-on experience building data pipelines that move data between on-premise systems and public cloud environments.

• Familiarity with vector databases, embedding models, and retrieval-augmented architectures.

• Experience applying AI agents to data quality, data profiling, or analytics workflows.

• Bachelor's degree in Computer Science, Machine Learning, Statistics, or a related quantitative discipline.

Job Expectations and Core Values:

• Be Humble: You're smart yet always interested in learning from others.

• Work Transparently: You always deal in an honest, direct, and transparent way.

• Take Ownership: You embrace responsibility and find joy in having the answers.

• Learn More: You regularly self-educate and improve your skill set.

• Show Gratitude: You show appreciation and respect to those you work with.

Hybrid Work Schedule with 3 days a week in office

Posting End Date:

*Job posting may come down early due to volume of applicants.