true Technical Architect - Artificial Intelligence - Digital Velocity
The Artificial Intelligence Technical Architect engages with clients and internal teams to provide design and engineering activities for Artificial Intelligence projects and solutions. This role is expected to be a thought leader in the areas of technical solutions provided for our customer. The Technical Architect is also responsible for working with OCTO and Management to align delivery teams on best practices and upskilling engineering resources.
Key Areas of Responsibility
- Professional services delivery for DV/CDW customers globally on major Public Cloud and on prem based AI platforms and solutions
- Aggregate oversight of technical solutions across multiple projects to ensure synergy in our approach and broad visibility to the solutions delivery team
- Works closely with the OCTO group for cohesive technical solution approaches focusing on bridging the gap between sales and delivery
- Focuses on technical standardization and opinionated approaches for client solutions
- Assists practice directors with technical growth plans for engineers and architects
- Assists with SOW reviews and approval as needed
- Assists with technical screening for new candidate interviews
- Proficient in AI platforms such as Google Vertex, Amazon SageMaker, Azure AI, KubeFlow
- Lead technical deployment engineering with customers on workload design on major public cloud and on prem based AI platforms and solutions
- Provide workshops and training events for customers and industry leaders on emerging AI platforms and solutions
- Training and mentoring Engineers to take on AI based projects
- Multi Cloud Consultant - Providing engineering services for GCP/Azure/AWS, coordinating engagement strategies, and qualifying technical resource requirements
- Performing billable work at other DV clients (Consulting Engagements)
- Presales consulting on occasion for AI projects
- Reviewing scopes and statements of work for AI projects
- Meet training and certification requirements for selected vendors (GCP AWS, Azure, Meta, IBM, Intel, NVIDIA etc.)
- Helping DV develop and mature our Cloud Engineering practice areas in response to client needs and market demand
- Proficient with Conversational AI and Generative AI
- Travel estimate is 10%
- Internal projects when applicable
Education and/or Skill-Set Qualifications
- Bachelor's degree in computer science or equivalent experience
- 7+ years of experience in deployment of private/public cloud solutions
- 7+ years of Providing Technical Guidance to other Engineers
- Knowledge and skill level in identified competencies meet minimum requirements for role
- Previous direct customer consulting experience or equivalent understanding of role responsibilities
- Demonstrated understanding of Terraform/Ansible or equivalent automation technologies
- Demonstrated knowledge of public cloud platforms, aware of multi-platform solutions and capabilities
- Highly proficient in at least one public cloud platform
- Demonstrated ability to speak to business value of public cloud solutions
- Excellent written and verbal communication skills, must be able to lead client facing conversations to drive success in consulting engagements
- Demonstrate solid interpersonal skills, able to mentor and guide internal engineering and personnel technical development teams
- Ability to understand, remember, and apply oral and/or written instructions or other information.
- Ability to organize thoughts and ideas into understandable terminology.
- Ability to multitask, organize and prioritize.
- Ability to apply common sense while engaging with customers and providing solutions.
- Ability to understand and follow complex instructions and guidelines.
- Public Cloud Certification: AWS/GCP/Azure
- Generative AI technologies such as large language models, prompt engineering, code generation text to image, and text to video.
- Experience working with LLM frameworks such as Langchain, LlamaIndex, or Haystack
- Experience with Pytorch, transformers, and pipelines
- Experience working with vector databases or other search technologies such as: AWS Kendra, OpenSearch, Azure Cognitive Services, and Google Vertex Search
- Experience with tools that manage and deploy AI/ML pipelines such as: Kubeflow and Kafka
- Training of AI/ML models such as LLMs or Image Generation
- Experience with Cloud AI platforms such as: Azure AI (including Cognitive Services), Google Vertex/Dialogflow, and Amazon SageMaker/Bedrock
- Additional technology areas and experience: Python, Cloud platform specific automation tooling, additional scripting languages, additional software development languages, data experience, networking experience, Docker, Kubernetes, CI/CD pipelines, Serverless Architectures
- Previous consulting experience