What are the responsibilities and job description for the Senior Generative AI Architect position at VBeyond Corporation?
Senior Generative AI Architect
New York City, NY
Full-Time Permanent
Job Description:
- We are seeking a Senior Generative AI Architect to define build and scale enterprise grade Generative AI solutions
- This role sits at the intersection of AI strategy handson engineering and business transformation You will lead GenAI initiatives end-to-end from ideation and architecture to production deployment while mentoring teams and shaping the organizations AI roadmap.
- This is a senior high impact role suited for a leader who can translate business problems into scalable GenAI solutions and guide stakeholders through responsible secure and value driven AI adoption
Key Responsibilities:
- Strategy Leadership.
- Define and own the Generative AI strategy and roadmap aligned to business priorities.
- Identify high value use cases across domains such as operations risk compliance customer experience and engineering productivity.
- Act as a thought leader on GenAI advising senior stakeholders on capabilities limitations and ROI.
- Establish AI governance responsible AI practices and model risk controls for enterprise use.
- Architecture Solution Design.
- Design and oversee end-to-end GenAI architectures including.
- Large Language Models LLMs.
- Retrieval Augmented Generation RAG.
- Agentic and multiagent workflows.
- Lead decisions on model selection finetuning prompt engineering and inference optimization.
- Ensure solutions meet enterprise standards for scalability security performance and observability.
- Handson Development.
- Lead and review implementation of GenAI solutions using Python and modern ML frameworks.
- Build and deploy APIs and services integrating GenAI into existing platforms and workflows.
- Partner with cloud teams to deploy solutions on AWS Azure or GCP using managed GenAI services.
- Guide teams through product ionization including monitoring evaluation and continuous improvement.
- Collaboration Enablement.
- Collaborate closely with Product Data Science Engineering Security Legal and Compliance teams.
- Mentor and upskill engineers data scientists and analysts in GenAI best practices.
- Establish reusable frameworks reference architectures and accelerators for GenAI adoption.
- Support client or internal stakeholder engagements including demos pilots and scaleout programs.