AI & Data Engineering Architect

Are you ready to make an impact at DTCC

Do you want to work on innovative projects, collaborate with a dynamic and supportive team, and receive investment in your professional development At DTCC, we are at the forefront of innovation in the financial markets. We are committed to helping our employees grow and succeed. We believe that you have the skills and drive to make a real impact. We foster a thriving internal community and are committed to creating a workplace that looks like the world that we serve.

Pay and Benefits:

• Competitive compensation, including base pay and annual incentive
• Comprehensive health and life insurance and well-being benefits, based on location
• Pension / Retirement benefits
• Paid Time Off and Personal/Family Care, and other leaves of absence when needed to support your physical, financial, and emotional well-being.
• DTCC offers a flexible/hybrid model of 3 days onsite and 2 days remote (onsite Tuesdays, Wednesdays and a third day unique to each team or employee).

The Impact you will have in this role:

The Development family is responsible for creating, designing, deploying, and supporting applications, programs, and software solutions. May include research, new development, prototyping, modification, reuse, re-engineering, maintenance, or any other activities related to software products used internally or externally on product platforms supported by the firm. The software development process requires in-depth subject matter expertise in existing and emerging development methodologies, tools, and programming languages. Software Developers work closely with business partners and / or external clients in defining requirements and implementing solutions. The Software Engineering role specializes in planning, documenting technical requirements, designing, developing, and testing all software systems and applications for the firm. Works closely with architects, product managers, project management, and end-users in the development and enhancement of existing software systems and applications, proposing and recommending solutions that solve complex business problems.

Key Responsibilities

• Lead the architecture, design, and implementation of enterprise-scale Agentic AI platforms and intelligent automation solutions that support critical business functions and data-driven decision making.
• Define and drive the organizations AI/ML architecture strategy, reference architectures, standards, and best practices across data, model, infrastructure, and governance layers.
• Design and implement advanced multi-agent systems using frameworks such as LangGraph, AutoGen, LlamaIndex, and emerging agent orchestration technologies.
• Architect complex Retrieval-Augmented Generation (RAG) solutions leveraging vector databases, knowledge graphs, semantic search, and enterprise data platforms.
• Develop scalable agentic workflows incorporating tool-calling, memory management, planning, reasoning, reflection, and human-in-the-loop capabilities.
• Lead the integration of LLM-powered applications utilizing Azure OpenAI, AWS Bedrock, and other enterprise AI services while ensuring performance, security, and cost optimization.
• Design enterprise-grade data architectures utilizing Snowflake, Apache Iceberg, Vector Databases, and cloud-native data platforms to support AI and analytics workloads.
• Establish standards and frameworks for model lifecycle management, experimentation, deployment, monitoring, observability, and governance using MLflow and modern MLOps practices.
• Define and implement enterprise AI security controls, including OAuth authentication, fine-grained authorization, role-based access control, data protection, and model governance frameworks.
• Drive AI platform modernization initiatives through containerization and orchestration technologies including Docker, Kubernetes, and cloud-native deployment architectures.
• Establish reusable patterns for Model Context Protocol (MCP) integration, external tool orchestration, AI application interoperability, and agent communication frameworks.
• Collaborate with business leaders, product owners, and engineering teams to identify AI transformation opportunities and translate business objectives into scalable technical solutions.
• Lead architectural reviews and provide technical oversight for AI/ML projects across multiple teams and business domains.
• Develop enterprise standards …