AI Engineer Consultant Job Description
Location: Phoenix, AZ (hybrid office schedule)
Employment Type: Full-time
Work Authorization: Applicants must have permanent authorization to work in the United States. Plex Consulting is unable to sponsor or transfer employment visas, or provide immigration-related employment sponsorship, now or in the future.
About the Role
We are seeking an AI Consultant to join our growing data engineering and analytics consultancy.
This is a hybrid strategist-builder role: you will advise enterprise clients on AI strategy and solution design while also architecting and implementing the resulting solutions. You will also have the opportunity to contribute to internal initiatives, helping shape how our organization builds and productizes AI capabilities.
This role is ideal for someone who is equally comfortable translating AI opportunities into business value in a boardroom and scoping production-grade data and AI architecture in a technical design session.
What You’ll Do
Strategy & Advisory
- Partner with client executives and stakeholders to identify, prioritize, and scope high-value AI and GenAI use cases aligned with business objectives.
- Develop AI/ML strategy roadmaps, maturity assessments, and business cases, including ROI, feasibility, and risk analyses, for enterprise clients.
- Advise clients on AI governance, responsible AI practices, data readiness, and the organizational change management needed to operationalize AI.
- Act as a trusted advisor in client meetings, workshops, and executive steering committees.
Solution Design
- Architect end-to-end AI/ML and data solutions, from data pipelines and feature engineering through model development, MLOps, and deployment.
- Translate ambiguous business problems into clear technical requirements, solution architectures, and delivery plans.
- Evaluate and recommend tools, platforms, and cloud AI services appropriate for client environments.
- Design solutions involving LLMs and GenAI, including RAG, agentic workflows, fine-tuning, and prompt engineering, where they align with client needs.
Implementation & Delivery
- Lead or contribute hands-on to the buildout of AI solutions, including data pipelines, model development, integration, and deployment into production.
- Write production-quality code and guide engineering teams on best practices.
- Manage technical delivery against scope, timeline, and budget; identify and mitigate project risks.
- Ensure solutions are scalable, secure, well-documented, and maintainable after handoff.
Internal Initiatives
- Contribute to internal AI capability building, including reusable frameworks, accelerators, reference architectures, and internal tooling.
- Mentor junior consultants and engineers on AI/ML methods and consulting best practices.
- Support internal AI adoption initiatives, such as applying AI to delivery, knowledge management, and operations.
- Contribute to practice development through point-of-view papers, case studies, proposal/RFP support, and pre-sales technical input.
Client & Business Development
- Support pre-sales activities, including scoping calls, technical proposals, estimating, and solution demos.
- Build long-term, trusted relationships with client stakeholders and identify opportunities to expand engagements.
- Represent Plex at client workshops, conferences, or industry events as needed.
What We’re Looking For
Required Qualifications
- Bachelor’s degree in Computer Science, Data Science, Engineering, or a related field, or equivalent practical experience.
- 5+ years of experience in data engineering, data science, ML engineering, or AI/analytics consulting, including direct client-facing experience.
- Demonstrated experience advising on AI/ML strategy and personally delivering technical implementations; candidates should not have a strategy-only or build-only background.
- Strong proficiency in Python and SQL, with hands-on experience using modern data pipelines and ML workflows.
- Practical experience with cloud platforms, such as AWS, Azure, or Google Cloud, and their AI/ML services.
- Solid understanding of the ML/AI lifecycle, including data preparation, model training and evaluation, deployment, monitoring, and retraining.
- Experience with modern GenAI/LLM technologies, including RAG architectures, vector databases, prompt engineering, and agentic frameworks.
- Excellent communication skills, with the ability to flex between technical depth with engineers and strategic framing with executives.
- Strong consulting fundamentals, including structured problem-solving, stakeholder management, and the ability to manage ambiguity.
Preferred Qualifications
- Prior experience at a consulting firm, systems integrator, or professional services organization.
- Experience leading workstreams or small teams on client engagements.
- Familiarity with data governance, AI risk/responsible AI frameworks, and enterprise data architecture.
- Relevant certifications, such as AWS, Azure, Google Cloud, ML, or Databricks certifications.
- Industry depth in one or more verticals, such as financial services, healthcare, retail, or manufacturing.
What Success Looks Like
- Clients view you as a trusted advisor who can both set direction and deliver results.
- Engagements you lead move smoothly from strategy and discovery into successful, production-grade implementation.
- Internal teams and junior staff grow their AI and data capabilities through your mentorship and reusable assets.
- You contribute to the firm’s AI practice growth through delivery excellence, thought leadership, and business development.