Principal Consultant - Artificial Intelligence (AI)
Based in United StatesFull-TimePrincipal
SalaryCompetitive salary range of approximately $170,000–$190,000 per year, based on experience.
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Job Details
- Experience
- 10+ years of consulting experience
- Required Skills
- AWSArtificial IntelligenceGCPMachine LearningMicrosoft AzureGenerative AI
Requirements
- 10+ years of consulting experience leading client workshops, discovery sessions, and executive-level advisory engagements.
- Proven background as an AI Architect, Solution Architect, or AI/ML Engineer with hands-on solution delivery experience.
- Strong expertise in designing enterprise AI systems, including generative AI, machine learning, and intelligent automation.
- Solid understanding of cloud architecture, data ecosystems, integration patterns, and security considerations.
- Experience translating complex technical concepts into clear business value narratives for senior stakeholders.
- Demonstrated ability to design or operate AI Centers of Excellence or similar enterprise AI governance structures.
- Familiarity with Microsoft Azure AI ecosystem, with additional exposure to AWS and/or GCP strongly preferred.
- Strong foundation in data management, including governance, lineage, and ML data readiness concepts.
- Excellent communication, facilitation, and stakeholder management skills at executive level.
- Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or related field.
Responsibilities
- Lead client discovery and AI readiness assessments, evaluating data, cloud, automation, governance, and organizational maturity.
- Translate business challenges into actionable AI opportunities, defining use cases, value hypotheses, and success metrics.
- Build and prioritize AI use case portfolios, conducting ROI analysis and developing executive-level roadmaps.
- Design end-to-end AI architectures, including generative AI, agentic systems, machine learning models, and automation workflows.
- Define scalable reference architectures, design patterns, and governance guardrails for secure and responsible AI adoption.
- Lead AI Center of Excellence (CoE) design and enablement, including operating models, intake processes, and governance frameworks.
- Advise executive stakeholders on AI strategy, operating models, risk management, and investment decisions.
- Collaborate with engineers, data teams, and platform specialists to ensure successful implementation of AI solutions.
- Contribute to reusable consulting frameworks, methodologies, and delivery accelerators for AI engagements.
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