Senior System Architect

About the role

We are At Synechron, we believe in the power of digital to transform businesses for the better. Our global consulting firm combines creativity and innovative technology to deliver industry-leading digital solutions. Synechron’s progressive technologies and optimization strategies span end-to-end Artificial Intelligence, Consulting, Digital, Cloud & DevOps, Data, and Software Engineering, servicing an array of noteworthy financial services and technology firms. Through research and development initiatives in our FinLabs we develop solutions for modernization, from Artificial Intelligence and Blockchain to Data Science models, Digital Underwriting, mobile-first applications and more. Over the last 20+ years, our company has been honored with multiple employer awards, recognizing our commitment to our talented teams. With top clients to boast about, Synechron has a global workforce of 17,000+, and has 58 offices in 22 countries within key global markets.

Our challenge The Senior System Architect for an enterprise level Gen AI solution will be responsible for defining and evolving the end-to-end architecture of the enterprise AI platform supporting CFO, Treasury, Risk, and Finance use cases. The role drives platform strategy, application architecture, AI/LLM integration, agentic workflows, data architecture, security, scalability, and production engineering while ensuring alignment with enterprise standards and regulatory requirements. The architect will serve as the technical authority for the AI ecosystem that this application covers, including Knowledge Bases, RAG solutions, Agent Frameworks, MCP integrations, document intelligence, structured data intelligence, model orchestration, and platform modernization initiatives.

Responsibilities

• Own the target-state architecture and technical roadmap for the AI platform.
• Design scalable, resilient, and secure enterprise AI solutions.
• Define reference architectures, standards, patterns, and best practices.
• Lead architecture reviews, technology selection, and solution governance.
• Drive modernization initiatives across AI, cloud-native, and data platforms.
• Design solutions leveraging LLMs, RAG, Agentic AI, MCP, vector databases, and knowledge management frameworks.
• Architect multi-agent workflows for document intelligence, commentary generation, validation automation, and data analysis.
• Define model integration strategies with enterprise AI services.
• Guide implementation of prompt management, evaluation frameworks, model governance, and AI observability.
• Define architectures for structured and unstructured data ingestion.
• Design integrations with databases, Starburst, S3, FileNet, and enterprise knowledge repositories.
• Architect metadata generation, chunking, embeddings, vector storage, and retrieval strategies.
• Establish data quality, lineage, and governance standards.
• Lead architecture for OpenShift-based deployments and containerized workloads.
• Design scalable services utilizing Redis, Oracle, NetApp