PNC Bank
All Teams
PNC's Approach to AI Exploration
While PNC Bank prides itself for being “brilliantly boring” when it comes to managing the business, it is still a place of creativity and experimentation. Our sandbox, PNC Labs, is a lively, interesting place to play with artificial intelligence (AI), and we’re always looking for new, inquisitive talent to join. And it’s not just a matter of experimenting in a conceptual way. PNC software engineers and data scientists get to see those ideas come to fruition.
Close
Employee Reviews
Senthil Kumar Jeyachandran, a PNC senior software architect, has worked in IT for more than 20 years, starting his career at IBM. In his current role, he leads the solution architecture for Document AI and Conversational AI and uses PNC lab space to explore new ideas.
Having the ability to experiment in an environment and test in a safe space enables him and his team to refine their approach and model. With the freedom to play with ideas around products and services before starting to build, the result is a more high-performing, scalable solution for the business.
Close
Senior Data Scientist Robert Smith is a former business analyst who likes the diversity of projects that comes in working on the client side at PNC. Smith works with AI in PNC’s Intelligent Automation team. Its mission is simple: apply ingenuity around how we do business. His team acts as internal consultants. The lines of business will come with an idea, and the team will offer up data scientists like Smith to analyze possible solutions. They get to work in a sandbox environment and conduct analytics that help move the needle forward.
Recently posted jobs
Machine Learning • Payments • Security • Software • Financial Services
Lead and mature detection and incident response lifecycle, run day-to-day SOC operations, manage on‑call readiness, drive SIEM detections and automation, coordinate cross‑team responses, maintain playbooks and run readiness exercises, mentor analysts, and ensure regulatory and post‑incident improvements.
19 Minutes AgoSaved
Machine Learning • Payments • Security • Software • Financial Services
Leads teams designing and delivering enterprise-scale batch and real-time data engineering platforms. Defines data product roadmaps, architects Kafka-based event-driven systems, builds high-throughput pipelines, establishes streaming standards and governance, and develops interoperable, AI-ready data products. Oversees organizational data policies, architecture, integrity, storage, and information management while partnering with engineering, architecture, product, and banking stakeholders.
Machine Learning • Payments • Security • Software • Financial Services
Owns the vision, backlog, priorities, and delivery outcomes for an enterprise backend platform. Acts as the voice of business and customer needs, translates requirements into actionable product direction, partners with Scrum Masters and Agile teams, accepts completed product increments, and communicates business value to stakeholders. The role requires strong business analysis, technical aptitude, risk awareness, stakeholder communication, and proficiency with Jira, Confluence, Change Navigator, and Microsoft Office.
