Vice President, Full-Stack Engineer
About The Position
We’re seeking a future team member for the role of 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 by championing Engineering 2.0 practices by embedding AI-augmented development workflows across the team, driving measurable gains in velocity, quality, and innovation. You will leverage AI coding assistants (Windsurf, Claude Code) and Model Context Protocols (MCPs) to accelerate software delivery, automate repetitive tasks, and elevate engineering standards. You will design and develop applications using LLM based AI models with RAG/Autogen and prompt engineering for Cybersecurity. You will architect, develop, and implement AI / ML powered cybersecurity solutions that integrate with internal and third-party applications. You will analyze the 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. You will collaborate cross-functionally to embed RAG- enabled LLM's features into product/application. You will lead technical workshops and knowledge-sharing sessions on AI-augmented development, machine learning integration for Cybersecurity use cases. You will mentor and uplift team members in adopting AI-driven engineering practices, fostering a culture of continuous learning and experimentation. You will 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 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 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
Responsibilities
- 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 standards
- Design, 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 applications
- Analyze 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 data
- Collaborate 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 experimentation
- Collaborate with the team and wider development community to cultivate Agile mindsets and practices, driving effective and adaptive workflows
Benefits
- highly competitive compensation
- benefits
- wellbeing programs
- access to flexible global resources and tools
- generous paid leaves
- paid volunteer time
- medical, dental, vision, and basic life insurance plans
- various paid time off benefits, such as vacation and sick time
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
