The AI Solutions Architect Director is the senior technical leader of Elliott Davis’s AI Strategy & Execution practice, part of the firm's overall Digital Practice. This is a hands-on, client-facing role responsible for taking client engagements from discovery through production delivery, designing AI-enabled workflows and agentic solutions that integrate with clients' existing technology stacks. 

The Director will set the standards, patterns, and reusable assets that define how Elliott Davis builds AI. They will architect solutions across the AI Value Path (Foundation, Capacity, Leverage, Advantage), guide technology decisions across Azure OpenAI, Copilot Studio, Power Automate, and adjacent platforms, and partner with other Elliott Davis practices to deliver integrated outcomes. 

This is a leadership role for the AI Strategy & Execution practice. Excellent technical judgment, executive communication, and the ability to lead teams through ambiguity are crucial for this role. 

Responsibilities

• Lead discovery workshops with client executives to translate business objectives, constraints, and success criteria into practical AI architectures and delivery roadmaps. 

• Own end-to-end solution design for AI-enabled workflows, agents, and copilots, including RAG patterns, orchestration, tool use, evaluation, guardrails, and human-in-the-loop design. 

• Deliver client engagements hands-on when required, writing code, building prototypes, and shipping production-grade solutions rather than only advising from a whiteboard. 

• Establish integration patterns with client enterprise systems (ERP, HCM, CRM, document management, identity, observability) so solutions are operable and supportable in production. 

• Set technical standards, reference architectures, and reusable accelerators that scale delivery quality across the practice. 

• Partner with growth leaders across the firm to shape and win new AI engagements, including scoping, estimating, proposal development, and executive presentations. 

• Collaborate with the Governance, Risk, and Compliance practice to embed responsible AI controls (NIST AI RMF, ISO 42001, model risk management) into every solution. 

• Coordinate across multiple consulting service lines to deliver integrated solutions aligned to the AI Value Path. 

• Engage, mentor, and grow a team of ready-now technical leaders, including AI engineers, integrations engineers, and solution architects. 
• Maintain trusted-advisor relationships with existing clients to renew and expand services. 

• Attend and speak at client, partner, and industry events to build the practice's technical brand. 

• Perform other duties as assigned within the scope of the practice. 

Requirements

• Minimum of a Bachelor's degree in Computer Science, Engineering, Information Systems, Data Science, or 12+ years of experience in software engineering, applied AI/ML, or enterprise solution architecture. 

• Minimum 3+ years of hands-on experience designing and shipping production AI/ML or generative AI solutions in enterprise environments, not only proofs of concept. 

• Minimum 2+ years leading technical teams, setting standards, and mentoring engineers and architects. 

• Strong programming background, with fluency in Python and comfort integrating with client systems through APIs, events, and modern data platforms. 

• Demonstrated ability to design agent-based and workflow automation solutions using orchestration frameworks such as LangChain, LangGraph, Semantic Kernel, or equivalent. 

• Deep working knowledge of at least one major cloud AI ecosystem (Azure OpenAI, AWS Bedrock, Google Vertex AI), including MLOps or LLMOps practices for model lifecycle, monitoring, and deployment. 

• Experience designing RAG architectures, vector stores, and evaluation frameworks for accuracy, cost, latency, and safety tradeoffs. 

• Excellent communication and presentation skills to all levels within an organization, including board level. Able to build relationships with senior stakeholders. 

• Experience partnering with security, privacy, and risk teams to embed responsible AI controls, access controls, auditability, and data handling into solution designs. 

• Experience building new products, services, or repeatable offerings. 

• Ability to take full ownership of client deadlines and needs, including working necessary hours to meet client deadlines. 

• Ability to work both independently and collaboratively within a team environment. 

Preferred but not Required:

• Prior professional services or consulting experience, including forward-deployed or client-embedded engineering roles. 

• Experience with Microsoft Copilot Studio, Power Automate, and the broader Microsoft AI stack. 

• Experience in regulated industries such as healthcare, financial services, or manufacturing. 

• Familiarity with financial close, R2R, or ERP-adjacent automation (Oracle FCCS, OneStream, Workday, NetSuite, or similar). 

• Relevant certifications (Azure AI Engineer, AWS Machine Learning, Google Professional ML Engineer, or equivalent). 
• Master's degree in Computer Science, Data Science, Engineering or related field.

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