Artificial Intelligence Consultant

Job Description

AI Delivery Transformation Consultant – AIDLC

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We are seeking experienced AI Delivery Transformation Consultants to help assess, validate, and certify teams operating within a new AI-driven delivery model. This role will focus on determining whether teams are truly adopting AI-enabled delivery practices in their day-to-day work, rather than relying solely on self-reported adoption.

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The ideal candidate brings a strong technical or architecture background, hands-on experience with AI-enabled software delivery, and the ability to evaluate how teams are actually using AI tools, agents, skills, plugins, and automated workflows.

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This is not a traditional Agile Coach role. We are looking for hands-on technical professionals who understand modern AI-driven SDLC practices and can objectively assess whether teams are changing how they build, deliver, and operate software.

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Key Responsibilities

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• Review teams that have self-reported operating at defined AIDLC accelerator maturity levels.

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• Validate whether teams are meaningfully incorporating AI skills, agents, plugins, and AI-driven workflows into their daily delivery practices.

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• Assess team workflows, delivery processes, technical practices, and outcomes to determine actual adoption.

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• Confirm that AI tools and plugins are properly registered within the enterprise AI catalog and aligned with the governed technology path.

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• Evaluate whether team structures align with the intended AI accelerator model, including smaller, more efficient delivery pods versus traditional large teams.

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• Use telemetry, delivery data, documentation, team discussions, and other evidence to validate adoption.

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• Pressure test and refine existing AIDLC maturity levels and certification criteria.

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• Help establish clear standards for what “good” looks like in AI-enabled software delivery.

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• Identify gaps between self-reported adoption and actual implementation.

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• Provide actionable feedback to teams and leadership regarding maturity, adoption, and areas for improvement.

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• Feed insights and lessons learned back into enterprise AI guidance, governance, and operating model refinement.

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• Partner with technical and business stakeholders across multiple teams and lines of business.

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• Facilitate assessments in a constructive manner while maintaining an objective and evidence-based approach.

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Required Qualifications

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• Hands-on experience delivering software or technology solutions using AI-enabled development practices.

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• Strong technical, engineering, architecture, or software development background.

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• Experience with AI-driven SDLC/AIDLC practices.

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• Practical experience using AI coding tools, AI agents, skills, plugins, and workflow automation in day-to-day delivery.

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• Ability to evaluate technical workflows, telemetry, delivery evidence, and outcomes.

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• Experience assessing whether teams are genuinely changing how they build and deliver technology.

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• Strong understanding of modern software engineering and delivery methodologies.

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• Ability to operate effectively in ambiguous and evolving environments.

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• Strong analytical and problem-solving skills with the ability to distinguish meaningful adoption from surface-level or self-reported adoption.

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• Ability to quickly understand existing frameworks and contribute with minimal ramp-up time.

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• Strong communication skills and the ability to work effectively with both technical teams and senior stakeholders.

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Preferred Qualifications

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• Experience with AI governance, auditability, responsible AI, or enterprise AI controls.

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• Familiarity with AI catalogs, plugin ecosystems, and governed AI technology environments.

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• Experience developing or evaluating technology maturity models, certification frameworks, or assessment methodologies.

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• Experience working across large enterprises, multiple business units, or complex technology organizations.

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• Experience with AI-assisted software engineering and developer productivity platforms.

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• Strong facilitation and stakeholder management skills.

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• Ability to challenge teams and validate evidence without creating a punitive or audit-focused environment.

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