Job Description:

Essential Job Functions:

• Design, develop, and maintain scalable document ingestion and processing pipelines to support enterprise knowledge management and AI-powered applications.
• Build and optimize multi-stage data workflows for extracting, transforming, enriching, and indexing content from diverse document formats including PDF, PPTX, DOCX, CSV, and image-based sources.
• Implement advanced document processing capabilities, including metadata extraction, content chunking, classification, summarization, and information retrieval workflows.
• Manage vector database indexing strategies and search optimization to ensure high-quality retrieval performance and relevance.
• Develop and maintain MCP-compatible tool servers that securely expose enterprise databases, APIs, cloud platforms, and external services to AI agents.
• Design and implement event-driven architectures leveraging messaging and integration services to enable scalable and responsive data processing solutions.
• Create and deploy data analysis, document intelligence, and knowledge retrieval agents using reusable development templates and platform tooling.
• Collaborate with cross-functional teams to deliver reliable, scalable, and innovative data engineering and AI-driven solutions.

Basic Qualifications:
• Bachelor's degree in Computer Science, Data Engineering, Information Technology, Artificial Intelligence, or equivalent combination of education and experience.
• Typically, 3+ years of professional experience in Python development and data pipeline engineering.
• Hands-on experience designing and maintaining ETL/ELT workflows using orchestration platforms such as Dagster, Airflow, or equivalent technologies.
• Strong proficiency with document processing frameworks and libraries for extracting and transforming content from structured and unstructured data sources.
• Experience working with vector databases, embedding models, semantic search technologies, and retrieval optimization techniques.
• Familiarity with Azure data and AI services, including Azure AI Search, Blob Storage, Event Hub, Document Intelligence, or comparable cloud-native platforms.
• Proven experience developing containerized applications and pipeline components using Docker and modern deployment practices.
• Strong understanding of REST API design, integration patterns, and service-oriented architectures.
• Experience building scalable ingestion, indexing, and retrieval systems for data-intensive applications.

Other Qualifications:
• Experience with Retrieval-Augmented Generation (RAG) architectures and enterprise knowledge management platforms is a plus.
• Familiarity with event-driven system design and distributed data processing patterns is preferred.
• Knowledge of AI agent ecosystems, MCP integrations, and modern data-to-agent architectures is highly desirable.
• Strong analytical, troubleshooting, and problem-solving skills.
• Excellent communication and collaboration abilities across technical and business stakeholders.
• Relevant certifications in Azure, Data Engineering, Artificial Intelligence, or Cloud Technologies are a plus.

At DXC Technology, we believe strong connections and community are key to our success. Our work model prioritizes in-person collaboration while offering flexibility to support wellbeing, productivity, individual work styles, and life circumstances. We’re committed to fostering an inclusive environment where everyone can thrive.

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