Solutions Architect (AI) - 622

DSM-H Consulting; Irving (TX); On-site; USD 150,000 - 210,000; Full time

Job summary

DSM-H Consulting is seeking a senior Enterprise AI Architect to lead solution definition for Generative AI and data use cases. You will engage with architects, stakeholders, and development teams to assess needs, translate requirements into practical architectures, and guide implementation across hybrid environments.

The role emphasizes discovery, architecture, and guidance rather than hands-on coding, with collaboration across AI COE teams.

Qualifications

• Design and implement enterprise AI and Generative AI solutions across on-prem and cloud.
• Facilitate discovery sessions and translate requirements into architecture.
• Guide internal teams through implementation planning and prototyping.
• Collaborate with business stakeholders and technical teams effectively.

Responsibilities

• Partner with architects and technical teams to shape solution approaches for new business use cases.
• Participate in discovery sessions with stakeholders to understand objectives and constraints.
• Translate requirements into architecture recommendations and implementation considerations.
• Collaborate with cross-functional teams to refine solution direction and support delivery planning.
• Create reference implementations or lightweight prototypes to illustrate approaches.
• Assess options, dependencies, and feasibility across hybrid environments.
• Clarify use case scope and next steps with stakeholders.
• Support evaluation of tools, platforms, and solution patterns per governance standards.
• Create documentation for proposed solutions, including architecture views and dependencies.
• Contribute to reusable architecture guidance and design patterns.

Skills

Enterprise AI design

Discovery facilitation

Hybrid cloud design

Implementation guidance

Prototyping

Communication skills

Education

Bachelor's degree

Tools

Azure

AWS

GCP

APIs & Microservices

Containerization

Cloud-native architectures

Identity & Security integration

Job description

• This role is intended for someone who can quickly engage with architects, business stakeholders, and internal development teams to assess needs, evaluate solution options, and define practical solution approaches for enterprise AI and data use cases, including Generative AI.
• Success in this role requires strong discovery, solution architecture, and cross-team collaboration skills.
• The role operates across hybrid on-premises and cloud environments and supports solution definition using approved enterprise platforms, services, and architectural patterns.
• It is primarily focused on discovery, solution architecture, and implementation guidance rather than hands‑on model development or day‑to‑day application coding.

Typical task breakdown

• Partner with existing architects and technical teams to shape solution approaches for new and evolving business use cases.
• Participate in discovery sessions with business stakeholders to understand objectives, pain points, constraints, and desired outcomes for proposed use cases.
• Translate business and functional requirements into solution concepts, architecture recommendations, and implementation considerations that align with enterprise standards.
• Collaborate with cross‑functional teams, including architects, internal development teams, engineers, data scientists, machine learning engineers, and domain experts, to refine solution direction, provide implementation guidance, and support delivery planning.
• Create or demonstrate reference implementations or lightweight prototypes, when appropriate, to illustrate recommended approaches for new or evolving use cases.
• Assess solution options, tradeoffs, dependencies, and technical feasibility for proposed business use cases across hybrid enterprise environments.
• Facilitate alignment between business stakeholders and technical teams by clarifying use case scope, assumptions, constraints, and recommended next steps.
• Support evaluation and recommendation of approved tools, platforms, and solution patterns needed to enable business use cases in alignment with enterprise architecture and governance standards.
• Create clear documentation for proposed solutions, including architecture views, assumptions, dependencies, design considerations, and recommended implementation approaches.
• Contribute to reusable architecture guidance, design patterns, and solution documentation that can support repeatable delivery across similar AI and data use cases.

Interaction with team

• Working with AI COE team members that consists for platform and application developers

Work environment

5 days in office ( no exceptions)

Education & Experience Required

• Bachelor’s degree with 10 years of more of experience in this capacity.
• Any Cloud certification is a nice to have.

Required Technical Skills

(Required)

• Proven experience designing and implementing enterprise AI and Generative AI solutions, including familiarity with enterprise AI platforms, model integration patterns, solution architecture considerations for production use cases, and modern AI solution approaches such as NLP, RAG, vector‑based search, enterprise search, prompt orchestration, agentic AI patterns, multi‑agent workflows, and orchestration concepts.
• Experience facilitating discovery sessions, gathering business and functional requirements, and translating them into solution architecture recommendations and implementation considerations.
• Experience designing scalable enterprise solutions across on‑premises and cloud environments, including familiarity with distributed computing platforms such as Microsoft Azure, AWS, and/or Google Cloud Platform (GCP), and modern application and integration patterns such as APIs, microservices, containerized workloads, cloud‑native architectures, and enterprise identity/security integration.
• Experience guiding internal development teams through implementation planning and solution alignment, including the ability to create reference implementations or lightweight prototypes and apply programming languages and common tools used in enterprise AI and cloud solution development.
• Ability to create reference implementations or lightweight prototypes to help internal development teams understand and apply recommended solution patterns for new use cases.
• Strong communication, facilitation, and collaboration skills, including the ability to work effectively with both business stakeholders and technical teams.

Preferred Qualifications

• Experience with specific technologies, platforms, frameworks, and specialized approaches such as Azure OpenAI, Amazon Bedrock, Vertex AI, AI Refinery, Microsoft Foundry, LangChain, LangGraph, GraphRAG, Snowflake, Dataiku, Agent Skills/agent harness patterns, MCP servers, and similar enterprise AI and data platforms.
• Experience with container platforms, orchestration technologies, or scalable deployment patterns such as Kubernetes, AKS, EKS, or similar enterprise hosting environments.
• Experience developing reusable architecture patterns, reference implementations, or solution accelerators to support adoption across multiple teams or business use cases.