GenAI & Agentic AI Engineer

PNC; United States; On-site; USD 75,000 - 138,000; Full time

Job summary

PNC is seeking a Software Engineer to design, develop, and deploy AI-powered applications and agentic systems leveraging large language models, orchestration frameworks, and enterprise data platforms.

You will work with data scientists, data engineers, and business stakeholders to translate needs into scalable AI solutions, monitor production AI solutions, and drive reliability and performance improvements.

Qualifications

• Hands-on experience developing applications in Python.
• Experience building or integrating AI, ML, Generative AI, or LLM-based solutions.
• Experience with agent orchestration frameworks such as LangGraph and LangChain.
• Experience developing and consuming REST APIs.
• Knowledge of Model Context Protocol (MCP) concepts and AI tool integrations.
• Experience deploying and supporting production software solutions.

Responsibilities

• Design, build, test, and deploy AI agents and GenAI-driven applications.
• Develop agentic workflows utilizing orchestration frameworks like LangGraph and LangChain.
• Build integrations with internal and external systems through REST APIs and other interfaces.
• Implement MCP-based solutions and integrations for AI workflows.
• Develop AI-powered automation for data and analytics use cases.
• Collaborate with data scientists to operationalize AI models and measure business impact.
• Monitor deployed AI agents using observability and telemetry tools.
• Troubleshoot, optimize, and maintain AI applications in production environments.
• Partner with data engineers and analytics teams to automate data workflows.
• Contribute to best practices for AI engineering, model governance, scalability, and software development.

Skills

Python

AI/ML/LLM

LangGraph

LangChain

REST APIs

MCP concepts

Production deployment

Education

Bachelor’s

Job description

PNC is seeking a Software Engineer to design, develop, and deploy AI-powered applications and agentic systems leveraging large language models, orchestration frameworks, and enterprise data platforms.

You will work with data scientists, data engineers, and business stakeholders to translate needs into scalable AI solutions, monitor production AI solutions, and drive reliability and performance improvements.