GenAI Customer Engineer

Veriipro; Irving (TX); On-site; USD 120,000 - 180,000; Full time

Job summary

Veriipro in Irving, TX seeks an experienced GenAI Customer Engineer to design and guide the implementation of Generative AI solutions for clients. You will translate business requirements into scalable, production-ready AI systems and collaborate with cloud teams to align infrastructure with GenAI needs.

You will work on architecture diagrams, technical design documents, and enable clients through workshops and demonstrations, ensuring secure, cost-effective deployments across enterprise

Qualifications

• 6–10 years in software/cloud/solution architecture roles.
• Strong understanding of Generative AI, LLMs, and enterprise patterns.
• Experience designing client-facing or enterprise-scale architectures.
• Familiarity with RAG, vector databases, embeddings, semantic search.
• Experience with AWS, Azure, or Google Cloud.

Responsibilities

• GenAI Solution Architecture: Design and recommend client-facing Generative AI solution architectures aligned with business objectives and technical requirements.
• Use Case Assessment: Understand client requirements, identify suitable GenAI use cases, and evaluate technical feasibility, business value, and implementation trade-offs.
• Solution Design: Develop architecture designs for LLM-based applications, Retrieval-Augmented Generation (RAG), AI assistants, chatbots, and other relevant GenAI solutions.
• Cloud and AI Platform Alignment: Recommend appropriate cloud infrastructure, GenAI services, foundation models, and supporting technologies based on client requirements.
• Technical Advisory: Provide technical consultation to clients on GenAI capabilities, solution patterns, architecture decisions, scalability, security, performance, and cost optimization.
• Implementation Guidance: Support development teams throughout solution implementation, integration, testing, deployment, and production readiness.
• End-to-End Validation: Validate solution components and workflows to ensure they meet functional, technical, performance, and quality expectations.
• Architecture Documentation: Create solution architecture diagrams, technical design documents, implementation guidelines, and other technical deliverables.
• Client Enablement: Conduct technical workshops, knowledge-sharing sessions, and demonstrations to help clients understand and adopt GenAI solutions.
• Stakeholder Collaboration: Collaborate with business stakeholders, architects, developers, data engineers, and cloud teams to ensure successful solution delivery.

Skills

GenAI concepts

LLMs

Prompt engineering

Solution architecture

Cloud platforms

API integration

Retrieval systems

RAG architectures

Enterprise AI

Stakeholder comms

Client-facing

Team collaboration

Security considerations

Tools

Vector databases

Embeddings

Semantic search

RAG

Foundation models

Job description

We are seeking an experienced GenAI Customer Engineer to design, develop, and guide the implementation of Generative AI solutions for clients. The ideal candidate will have strong solution architecture skills, expertise in cloud and GenAI platforms, and the ability to translate business requirements into scalable, secure, and production-ready AI solutions.

Key Responsibilities

• GenAI Solution Architecture: Design and recommend client-facing Generative AI solution architectures aligned with business objectives and technical requirements.
• Use Case Assessment: Understand client requirements, identify suitable GenAI use cases, and evaluate technical feasibility, business value, and implementation trade-offs.
• Solution Design: Develop architecture designs for LLM-based applications, Retrieval-Augmented Generation (RAG), AI assistants, chatbots, and other relevant GenAI solutions.
• Cloud and AI Platform Alignment: Recommend appropriate cloud infrastructure, GenAI services, foundation models, and supporting technologies based on client requirements.
• Technical Advisory: Provide technical consultation to clients on GenAI capabilities, solution patterns, architecture decisions, scalability, security, performance, and cost optimization.
• Implementation Guidance: Support development teams throughout solution implementation, integration, testing, deployment, and production readiness.
• End-to-End Validation: Validate solution components and workflows to ensure they meet functional, technical, performance, and quality expectations.
• Architecture Documentation: Create solution architecture diagrams, technical design documents, implementation guidelines, and other technical deliverables.
• Client Enablement: Conduct technical workshops, knowledge-sharing sessions, and demonstrations to help clients understand and adopt GenAI solutions.
• Stakeholder Collaboration: Collaborate with business stakeholders, architects, developers, data engineers, and cloud teams to ensure successful solution delivery.

Required Skills and Qualifications

• 6–10 years of experience in software engineering, cloud engineering, solution architecture, AI/ML engineering, or related technical roles.
• Strong understanding of Generative AI concepts, Large Language Models (LLMs), prompt engineering, and enterprise AI solution patterns.
• Experience designing technical architectures for client-facing or enterprise-scale solutions.
• Familiarity with RAG architectures, vector databases, embeddings, semantic search, and knowledge retrieval systems.
• Experience with one or more major cloud platforms: AWS, Microsoft Azure, or Google Cloud Platform.
• Understanding of API integration, microservices, distributed systems, and application architecture.
• Ability to assess technical options and explain architectural trade-offs to technical and non-technical stakeholders.
• Experience creating architecture diagrams, technical specifications, solution design documents, and implementation guides.
• Strong communication, presentation, problem-solving, and client-facing consulting skills.
• Ability to work collaboratively with cross-functional teams and support multiple phases of solution delivery.