W-2 ONLY NO SUBS, NO Subcontract companies.
Hybrid onsite 3 days a week in Houston Office
Initial Project Phase: Six weeks
The initial engagement will focus on validating the end-to-end audit process, confirming data accessibility and integration readiness, and demonstrating the feasibility of the proposed AI capabilities through a working proof of concept.
- Senior Solution Architect with strong enterprise solution architecture experience and hands-on exposure to AI/GenAI solutions, data integration, and technical feasibility assessments.
- Must have experience designing AI-enabled applications or workflows, including AI agents or LLM-based solutions;
- strong understanding of APIs, data architecture, cloud platforms (Azure/AWS), data accessibility, security, and integration requirements.
- Proven experience leading technical discovery, evaluating solution feasibility, and supporting working POCs.
- Must be able to translate business processes into technical architecture, identify risks and dependencies, and communicate recommendations to senior business and technical stakeholders.
- Experience working within enterprise architecture standards and governance frameworks.
Automatic rejections reasons candidate not qualified for this role/team:
- General IT architects with no AI/GenAI solution experience;
- data engineers or developers without solution architecture ownership;
- AI/ML researchers focused only on modeling rather than enterprise integration;
- candidates with only theoretical AI knowledge or prompt engineering experience;
- cloud infrastructure architects without application/data integration experience;
- candidates unable to demonstrate end-to-end solution design,
- technical feasibility assessments, or stakeholder-facing architecture decisions;
- junior/mid-level profiles without enterprise architecture experience.
This role will focus on evaluating solution feasibility, assessing data and integration requirements, and designing an architecture that supports the development and validation of AI-driven audit capabilities.
The Solution Architect will work closely with business stakeholders, technical teams, and external partners to translate business requirements into practical technical solutions while ensuring alignment with enterprise architecture standards.
The initial project phase is a six-week engagement focused on validating the proposed solution through a working proof of concept (POC) before proceeding with broader infrastructure investment and implementation.
Key Responsibilities
Solution Architecture & Technical Design
- Lead the development and evaluation of solution architectures supporting AI-enabled audit processes.
- Translate business requirements into scalable, secure, and technically feasible architecture designs.
- Assess proposed solutions for alignment with enterprise architecture standards, technology roadmaps, and integration frameworks.
- Identify technical dependencies, architectural risks, and potential implementation challenges.
- Provide technical recommendations to support solution selection and future implementation decisions.
AI Proof of Concept & Feasibility Assessment
- Support the design and development of a working AI proof of concept to validate core audit capabilities.
- Evaluate the feasibility of using AI agents to support and automate defined audit activities.
- Collaborate with technical teams to establish POC requirements, success criteria, and validation approaches.
- Assess solution performance, technical limitations, and readiness for future development.
- Provide recommendations regarding infrastructure requirements, scalability, and next steps following POC evaluation.
Data & Integration Architecture
- Evaluate existing data sources, accessibility, quality, and integration readiness.
- Identify data dependencies and integration requirements necessary to support AI-enabled workflows.
- Design and recommend appropriate data integration approaches across relevant systems and platforms.
- Collaborate with data engineering and development teams to address technical challenges and validate solution feasibility.
- Ensure proposed solutions consider data security, governance, and enterprise integration standards.
Stakeholder Engagement & Architecture Governance
- Partner with business leaders, project teams, and technical stakeholders to understand requirements and align solution design with business objectives.
- Communicate architecture decisions, technical risks, and recommendations to both technical and nontechnical audiences.
- Provide technical guidance and architectural oversight throughout the POC engagement.
- Develop and maintain relevant architecture documentation, including solution designs, integration diagrams, and technical recommendations.
- Ensure solutions follow applicable architecture standards and governance processes, escalating exceptions when necessary.
Required Qualifications
- Demonstrated experience in solution architecture, including designing and evaluating enterprise IT solutions.
- Strong understanding of AI-enabled applications, data integration architecture, and enterprise technology environments.
- Experience assessing technical feasibility and translating business requirements into solution designs.
- Knowledge of data architecture, system integrations, APIs, and application architecture principles.
- Experience supporting proof-of-concept initiatives, solution evaluations, or early-stage technology implementations.
- Strong stakeholder management skills with the ability to engage business leaders, technical teams, and external partners.
- Excellent written and verbal communication skills, including the ability to present complex technical concepts to diverse audiences.
- Ability to work independently, provide technical leadership, and make informed architecture recommendations.
Preferred Qualifications
- Experience designing or evaluating generative AI, AI agents, or AI-driven workflow automation solutions.
- Familiarity with cloud architecture, enterprise integration platforms, and AI/ML technologies.
- Experience with data governance, security, and access management considerations for AI applications.
- Knowledge of enterprise architecture frameworks and tools such as IBM System Architect, PowerDesigner, or ProVision.
- Experience supporting audit, compliance, or business process automation initiatives.