- 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).
Core Competencies
Demonstrates expertise in designing and implementing AI architectures and workflows, with a strong focus on production-grade solutions and integration with enterprise systems. Proven ability to lead technical teams, mentor engineers, and establish standards for quality delivery in AI engagements.
Highest-signal resume keywords
- AI Architecture Design
- Production AI/ML Solutions
- Python Programming
- Cloud AI Ecosystem Expertise
- Team Leadership and Mentoring
ATS Optimization Keywords
Hard Skills
- AI Workflow Automation
- RAG Architecture Design
- API Integration
- Orchestration Frameworks
- MLOps Practices
- Model Risk Management
- Evaluation Frameworks
- Data Handling Controls
- Generative AI Solutions
- Vector Store Design
Soft Skills
- Excellent Communication
- Relationship Building
- Presentation Skills
- Collaboration
- Mentoring
Certifications & Qualifications
- Azure AI Engineer
- AWS Machine Learning
- Google Professional ML Engineer
Industry Keywords
- Enterprise Solution Architecture
- Regulated Industries
- Healthcare
- Financial Services
- Manufacturing
Tools & Technologies
- Microsoft Copilot Studio
- Power Automate
- Azure OpenAI
- AWS Bedrock
- Google Vertex AI
- LangChain
- LangGraph
- Semantic Kernel
- ERP Systems
- Document Management Systems