Vice President, AI-Augmented Full-Stack Engineer

About the role

We’re seeking an AI-Augmented Full-Stack Engineer to join our Cyber Detection and Response Team in Pittsburgh, PA, or Lake Mary, FL. In this role, you’ll make an impact by:

• Championing Engineering 2.0 practices by embedding AI-augmented development workflows across the team, driving measurable gains in velocity, quality, and innovation.
• Leveraging AI coding assistants (Windsurf, Claude Code) and Model Context Protocols (MCPs) to accelerate software delivery, automate repetitive tasks, and elevate engineering standards.
• Designing and developing applications using LLM-based AI models with RAG/Autogen and prompt engineering for cybersecurity.
• Architecting, developing, and implementing AI/ML-powered cybersecurity solutions that integrate with internal and third-party applications.
• Analyzing model output to define, create, and maintain meaningful insights to support advanced analytics.
• Unlocking the full potential of AI to accurately extract data, automate tasks, and gain deeper insights from data.
• Collaborating cross-functionally to embed RAG-enabled LLM features into products/applications.
• Leading technical workshops and knowledge-sharing sessions on AI-augmented development and machine learning integration for cybersecurity use cases.
• Mentoring and uplifting team members in adopting AI-driven engineering practices, fostering a culture of continuous learning and experimentation.
• Collaborating with the team and wider development community to cultivate Agile mindsets and practices, driving effective and adaptive workflows.

Requirements

• Hands-on experience with machine learning concepts and the ability to integrate ML models into production applications and data pipelines.
• 5-6 years of strong hands-on experience in Python, Java programming, service-oriented architecture, REST API, and knowledge of AI/ML concepts and their applications.
• 1+ years of demonstrated experience building LLM and GenAI tools, including LangChain, RAG, fine-tuning, Agentic AI, prompt engineering, and vector databases.
• Proficiency in developing machine learning or LLM-based AI solutions (RAG or Autogen).
• Proficiency in scripting and SQL, Postgres for data management, vector databases for LLM Agents, and a strong understanding of the SDLC lifecycle and managing cloud deployments of containers.
• Strong technical foundation in computer science/systems engineering, with deep hands-on expertise in UNIX/Linux, networking, performance troubleshooting, and system integration through APIs across complex environments.
• Proven ability to build scalable, resilient cloud-native solutions using modern cloud and container platforms, supported by experience in DevOps and configuration management tools such as Git and Artifactory.
• Experience delivering high-volume, highly available enterprise applications in regulated environments.
• Experience with modern CI/CD pipelines and infrastructure-as-code tooling.
• Ability to communicate effectively with both technical and non-technical stakeholders.
• Excellent verbal and written communication skills.

About the Team

At BNY, our culture speaks for itself. Here’s a few of our recent awards:

• America’s Most Innovative Companies, Fortune, 2025
• World’s Most Admired Companies, Fortune 2025
• “Most Just Companies”, Just Capital and CNBC, 2025

Benefits

BNY offers highly competitive compensation, benefits, and wellbeing programs rooted in a strong culture of excellence and our pay-for-performance philosophy. Benefits include:

• Access to flexible global resources and tools for your life’s journey.
• Focus on health, personal resilience, and financial goals, including generous paid leaves (e.g., paid volunteer time).
• Eligibility for an annual discretionary incentive award.
• 401(k) plan participation.
• Company-sponsored medical, dental, vision, and basic life insurance plans for employees and eligible dependents.
• Various paid time off benefits, such as vacation and sick time, depending on the position.

Pay

BNY assesses market data to ensure a competitive compensation package. The expected base salary for this position may vary depending on market location, job-related knowledge, skills, and experience. Base salary is part of a total rewards package, which may include eligibility for an annual discretionary incentive award.