Senior AI Engineer – Agentic AI & Generative AI

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.

The Information Technology group delivers secure, reliable technology solutions that enable DTCC to be the trusted infrastructure of the global capital markets. The team delivers high-quality information through activities that include development of essential, building infrastructure capabilities to meet client needs and implementing data standards and governance.

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

Join our team to help deliver next-generation AI capabilities that transform how business processes are automated, optimized, and enhanced through Generative AI and Agentic AI solutions.

We are seeking a highly skilled Senior AI Engineer with hands-on experience designing, building, integrating, and deploying enterprise-scale AI applications. This role focuses on leveraging, integrating, and orchestrating existing foundation models and AI services to solve real business problems through intelligent agents, agentic workflows, Retrieval-Augmented Generation (RAG), and enterprise integrations.

Unlike traditional AI research roles, this position emphasizes the integration, orchestration, and operationalization of existing AI capabilities rather than the development of foundational models.

You will partner closely with software engineers, architects, data engineers, and business stakeholders to take AI solutions from concept and prototype through production deployment. The ideal candidate combines strong Python engineering skills with practical experience developing AI-powered applications using Amazon Bedrock, AWS, Snowflake, and modern agent development frameworks.

Your Primary Responsibilities Build Enterprise AI Solutions

• Design, develop, test, and deploy Generative AI and Agentic AI applications using Amazon Bedrock, AWS, and related AI technologies.
• Build intelligent AI agents and multi-agent systems that automate and enhance business workflows.
• Develop scalable AI-powered solutions that integrate seamlessly with enterprise applications and platforms.

Design Agentic Architectures

• Design and implement agent orchestration patterns, including: - Supervisor and coordinator agents
• Specialized task agents
• Routing and decisioning frameworks
• Context and memory management
• Workflow execution and monitoring
• Build multi-step reasoning workflows that effectively combine LLM intelligence with enterprise systems and business processes.

Develop AI Integrations

• Integrate AI agents with: - REST APIs
• Enterprise applications
• Internal platforms and services
• Databases and data platforms
• External tools and third-party systems
• Create secure and reusable tools, APIs, and integration layers that enable agent interaction with enterprise systems.

Implement Knowledge-Driven AI

• Design and deliver Retrieval-Augmented Generation (RAG) solutions using enterprise documents, structured data, and knowledge repositories.
• Implement embeddings, vector search, document retrieval, and knowledge-grounding strategies to improve AI accuracy and business outcomes.
• Select and leverage appropriate foundation models based on business and technical requirements.

Build Production-Ready AI Applications

• Develop backend AI services primarily using Python.
• Design prompts, agent instructions, tool definitions, workflows, and AI guardrails.
• Deploy and support AI applications within AWS and OpenShift (OCP) environments.
• Implement logging,…