AI Solutions Architect, Director

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.

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