VP of Solutions Architect - AI
New
J
JobgetherIT Security, AI
Based in United StatesFull-TimeVp
Salary not disclosed
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Job Details
- Experience
- 10+ years
- Required Skills
- PythonTerraformMLOpsGenerative AI
Requirements
- Bachelor’s degree in Computer Science, Engineering, or a related technical discipline, or equivalent practical experience.
- 10+ years of experience in software engineering, cloud architecture, or enterprise technology leadership roles.
- Extensive expertise designing and implementing AI solutions using cloud platforms and modern AI/ML services.
- Strong experience with generative AI architectures, agentic workflows, RAG systems, and AI orchestration patterns.
- Hands-on experience with cloud-native development, serverless architectures, distributed systems, and event-driven solutions.
- Proficiency with Infrastructure as Code tools such as Terraform, CloudFormation, or CDK.
- Strong programming skills in Python and experience working with cloud SDKs and AI development frameworks.
- Experience with machine learning platforms, model deployment, monitoring, and lifecycle management.
- Knowledge of security best practices, governance frameworks, compliance requirements, and responsible AI principles.
- Proven ability to lead enterprise-scale technology transformations and advise senior stakeholders.
- Exceptional communication, presentation, and collaboration skills across technical and executive audiences.
Responsibilities
- Serve as the primary technical advisor for strategic clients, leading AI architecture discussions from concept development to production implementation.
- Design advanced generative AI and agentic AI solutions using cloud-native AI services, including foundation models, retrieval-augmented generation (RAG), multi-agent systems, and orchestration frameworks.
- Create reference architectures, technical documentation, architecture decision records, and implementation roadmaps aligned with business objectives.
- Validate solution feasibility through hands-on prototyping, development, and experimentation using programming languages, AI SDKs, and cloud services.
- Ensure solutions follow cloud architecture best practices related to security, reliability, scalability, cost optimization, and operational excellence.
- Guide technical teams through complex architecture decisions involving AI models, performance requirements, governance, compliance, and infrastructure choices.
- Provide leadership and mentorship to engineering teams, helping establish best practices for AI engineering, MLOps, observability, and secure cloud development.
- Develop reusable accelerators, infrastructure modules, and automation frameworks to improve delivery efficiency.
- Support customer engagements, workshops, pre-sales activities, and strategic initiatives by translating technical concepts into business value.
- Collaborate with product, engineering, research, and customer-facing teams to continuously improve AI solution offerings and delivery capabilities.
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