Vice President, AI-Augmented Full-Stack Engineer

About the role

This role is located in Pittsburgh, PA, or Lake Mary, FL. In this position, you will champion Engineering 2.0 practices by embedding AI-augmented development workflows across the team, driving measurable gains in velocity, quality, and innovation.

Responsibilities

• Leverage AI coding assistants (Windsurf, Claude Code) and Model Context Protocols (MCPs) to accelerate software delivery, automate repetitive tasks, and elevate engineering standards.
• Design and develop applications using LLM-based AI models with RAG/Autogen and prompt engineering for Cybersecurity.
• Architect, develop, and implement AI/ML-powered cybersecurity solutions that integrate with internal and third-party applications.
• Analyze model output to define, create, and maintain meaningful insights to support advanced analytics.
• Unlock the full potential of AI to accurately extract data, automate tasks, and gain deeper insights from data.
• Collaborate cross-functionally to embed RAG-enabled LLM features into products/applications.
• Lead technical workshops and knowledge-sharing sessions on AI-augmented development and machine learning integration for Cybersecurity use cases.
• Mentor and uplift team members in adopting AI-driven engineering practices, fostering a culture of continuous learning and experimentation.
• Collaborate 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.
• Proficient in developing machine learning or LLM-based AI solutions (RAG or Autogen).
• Proficient in scripting and SQL, Postgres for data management, vector databases for LLM Agents, with 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.