Sr Data Science Engineer

CBC; Reston (VA); Híbrido; USD 120.000 - 180.000; Jornada completa

Descripción de la vacante

CBC is seeking a hands-on AI/data engineering expert to design and deliver AI-enabled data products. You will build scalable data pipelines, data models, and integrations while applying Gen AI, LLMs, and enterprise AI services across AWS-native infrastructure.

You will leverage Python and PySpark for data processing, analytics, and automation, designing APIs and integrations with enterprise systems. Strong communication skills are essential for collaboration with stakeholders and product teams.

Formación

• Hands-on Generative AI and LLM expertise.
• Strong data architecture and engineering skills for data pipelines, models, and scalable processing.
• Strong Python and PySpark development skills for data processing, analytics, automation, and AI-enabled applications.
• Experience designing AI-enabled products and translating business requirements into architectures.
• Strong API and systems integration experience including REST APIs and enterprise systems.
• Experience with cloud-native serverless architectures, including AWS Lambda, Glue, Step Functions, containers, and event-driven workflows.
• Excellent communication and written skills.

Responsabilidades

• Develop AI-enabled data products and analytics pipelines.
• Design scalable data models and integrations.
• Build with Python and PySpark for processing and automation.
• Implement AI services via REST APIs and enterprise systems.
• Architect cloud-native, serverless workflows on AWS.
• Communicate clearly with stakeholders.

Conocimientos

Gen AI/LLM

Python & PySpark

Data pipelines

APIs & integration

Cloud-native AWS

Communication

Herramientas

Bedrock

Lambda

Glue

Step Functions

Descripción del empleo

Location: Reston, VA (Hybrid) - Locals Only

Duration: Long term

Job Description

• Hands-on Generative AI and LLM expertise, including AI agents, Retrieval-Augmented Generation (RAG), Amazon Bedrock, and enterprise AI integration.
• Strong data architecture and engineering skills, including designing data pipelines, data models, integrations, and scalable processing of large datasets.
• Strong Python and PySpark development skills for data processing, analytics, automation, and AI-enabled applications.
• Experience designing AI-enabled products, translating business and product requirements into practical technical architectures and implementation approaches.
• Strong API and systems integration experience, including REST APIs and connecting applications, data platforms, AI services, and enterprise systems.
• Experience with modern cloud-native and serverless architectures, including AWS Lambda, Glue, Step Functions, containers, and event-driven workflows.
• Excellent communication and written skills