Senior AI Engineer – Agentic AI & Generative AI

The Depository Trust & Clearing Corporation (DTCC); Jersey City (NJ); Hybrid; USD 140,000 - 210,000; Full time

Benefits offered by this job

Flexible hybrid model

Job summary

DTCC in Jersey City seeks a Senior AI Engineer to architect and deploy enterprise-grade AI solutions. You will design, build, and operationalize Generative AI and agentic workflows, leveraging Bedrock, AWS, Snowflake, and OpenShift within production environments.

You will collaborate with software, data, and business teams to translate complex use cases into scalable, secure AI applications, implementing robust monitoring, governance, and guardrails while advancing DTCC's AI strategy.

Qualifications

• 6-8 years of hands-on experience in Software Engineering, AI Engineering, Data Engineering, or related technical disciplines.
• Demonstrated success delivering production-grade AI, Machine Learning, or Generative AI solutions.
• Experience translating business use cases into scalable AI-enabled applications.

Responsibilities

• 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 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 combine LLM intelligence with enterprise systems and business processes.
• Integrate AI agents with REST APIs, enterprise applications, internal platforms, databases, and external tools.
• Create secure and reusable tools, APIs, and integration layers for agent interactions with enterprise systems.
• Design and deliver Retrieval-Augmented Generation (RAG) solutions using enterprise documents and data.
• Implement embeddings, vector search, document retrieval, and knowledge-grounding strategies.
• Select and leverage foundation models based on business requirements.
• 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 environments.
• Implement logging, monitoring, security, observability, and operational controls for enterprise AI workloads.
• Collaborate across engineering, architecture, product, and business teams to identify and deliver AI-enabled solutions.
• Troubleshoot and resolve issues involving models, agents, APIs, integrations, and downstream systems.
• Establish reusable engineering patterns, best practices, and governance standards for Agentic AI development.
• Provide technical leadership and mentorship to engineers and development teams.

Skills

Python

AI Engineering

Team collaboration

Problem solving

Analytical skills

Communication

DevOps

Tools

Amazon Bedrock

AWS

Snowflake

OpenShift

Job description

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, monitoring, evaluation, security, observability, and operational controls for enterprise AI workloads.

Drive Engineering Excellence

• Collaborate across engineering, architecture, product, and business teams to identify and deliver AI-enabled solutions.


• Troubleshoot and resolve issues involving models, agents, APIs, integrations, and downstream systems.


• Establish reusable engineering patterns, best practices, and governance standards for Agentic AI development.


• Provide technical leadership and mentorship to engineers and development teams.

Qualifications

• 6-8 years of hands-on experience in Software Engineering, AI Engineering, Data Engineering, or related technical disciplines.


• Demonstrated success delivering production-grade AI, Machine Learning, or Generative AI solutions.


• Experience translating business use cases into scalable AI-enabled applications.

Talent Needed for Success

AI & Software Engineering

• Strong hands-on programming expertise in Python.


• Experience developing and deploying Generative AI and LLM-powered applications.


• Strong experience with Amazon Bedrock and AWS-based AI services.


• Experience designing and implementing AI agents and agentic workflows.


• Strong understanding of: - Agent orchestration


• Multi-agent architectures


• Tool/function calling


• Agent memory


• Context management


• Prompt engineering

AI & Data Platforms

• Hands-on experience with: - Retrieval-Augmented Generation (RAG)


• Embeddings


• Vector databases and vector search


• Knowledge retrieval systems


• Enterprise document processing


• Strong Snowflake, SQL, and data integration experience.

Enterprise Integration

• Experience integrating AI solutions with: - REST APIs


• Enterprise applications


• Databases


• Internal and external services


• Experience deploying, supporting, and monitoring AI solutions in production environments.

Security & Governance

• Strong understanding of: - Authentication and authorization


• Enterprise security and data privacy


• Secrets management


• Responsible AI practices


• AI governance and guardrails

Professional Skills

• Excellent analytical, problem-solving, and debugging skills.


• Strong verbal and written communication skills.


• Ability to effectively collaborate with engineering and business stakeholders.


• Demonstrated ability to work in fast-paced, highly collaborative environments.

Professional Skills

• Experience with Agentic AI frameworks such as: - CrewAI


• LangGraph


• AutoGen


• Similar orchestration frameworks


• Experience with Model Context Protocol (MCP).


• Experience building complex multi-agent collaboration systems.


• Experience with AI evaluation, monitoring, and observability frameworks.


• Experience using Kiro or other AI-assisted development tools.


• Experience with OpenShift (OCP), containers, and cloud-native deployments.


• Experience implementing CI/CD pipelines and DevOps practices for AI applications.


• Familiarity with Snowflake Cortex AI capabilities.


• Knowledge of enterprise AI governance, model monitoring, and responsible AI principles.

The salary range is indicative for roles at the same level across all US locations. Actual salary is determined based on the role, location, individual experience, skills, and other considerations. We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, sex, gender, gender expression, sexual orientation, age, marital status, veteran status, or disability status. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.