We’re seeking a future team member for the role of AI-Augmented Full-Stack Engineer to join our Cyber Detection and Response Team. This role is located in Pittsburgh, PA, or Lake Mary, FL.In this role, you’ll make an impact in the following ways: Champion Engineering 2.0 practices by embedding AI-augmented development workflows across the team, driving measurable gains in velocity, quality, and innovation.Leverage AI coding assistants (Windsurf, Claude Code) and Model Context Protocols (MCPs) to accelerate software delivery, automate repetitive tasks, and elevate engineering standardsDesign, develop application 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 applicationsAnalyze the model output to define, create, and maintain meaningful insights to support advanced analytics. Unlock the full potential of AI to accurate extract data, automate tasks and gain deeper insights from dataCollaborate cross-functionally to embed RAG- enabled LLM's features into product/application.Lead technical workshops and knowledge-sharing sessions on AI-augmented development, 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 experimentationCollaborate with the team and wider development community to cultivate Agile mindsets and practices, driving effective and adaptive workflows To be successful in this role, we’re seeking the following: Hands-on experience with machine learning concepts and the ability to integrate ML models into production applications and data pipelines.5-6 yrs of strong hands-on experience in Python, Java programming, service-oriented architecture, REST API and Knowledge of AI/ML concepts and it’s applications.1+ years 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, strong understanding of 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 environmentsExperience with modern CI/CD pipelines and infrastructure-as-code toolingAbility to communicate effectively with both technical and non-technical stakeholdersExcellent verbal and written communication skills