New York Technology Partners
Artificial Intelligence Consultant
Skills
18 days ago
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Important information
Contract type:
Freelance / Contract
Salary:
$104,000 – $124,800 / year
Location:
New York, NY, USA
Work mode:
Onsite
Published on:
9 October 2026
What they need
AI Delivery Transformation Consultant – AIDLC
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.
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.
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.
Key Responsibilities
- Review teams that have self-reported operating at defined AIDLC accelerator maturity levels.
- Validate whether teams are meaningfully incorporating AI skills, agents, plugins, and AI-driven workflows into their daily delivery practices.
- Assess team workflows, delivery processes, technical practices, and outcomes to determine actual adoption.
- Confirm that AI tools and plugins are properly registered within the enterprise AI catalog and aligned with the governed technology path.
- Evaluate whether team structures align with the intended AI accelerator model, including smaller, more efficient delivery pods versus traditional large teams.
- Use telemetry, delivery data, documentation, team discussions, and other evidence to validate adoption.
- Pressure test and refine existing AIDLC maturity levels and certification criteria.
- Help establish clear standards for what “good” looks like in AI-enabled software delivery.
- Identify gaps between self-reported adoption and actual implementation.
- Provide actionable feedback to teams and leadership regarding maturity, adoption, and areas for improvement.
- Feed insights and lessons learned back into enterprise AI guidance, governance, and operating model refinement.
- Partner with technical and business stakeholders across multiple teams and lines of business.
- Facilitate assessments in a constructive manner while maintaining an objective and evidence-based approach.
Required Qualifications
- Hands-on experience delivering software or technology solutions using AI-enabled development practices.
- Strong technical, engineering, architecture, or software development background.
- Experience with AI-driven SDLC/AIDLC practices.
- Practical experience using AI coding tools, AI agents, skills, plugins, and workflow automation in day-to-day delivery.
- Ability to evaluate technical workflows, telemetry, delivery evidence, and outcomes.
- Experience assessing whether teams are genuinely changing how they build and deliver technology.
- Strong understanding of modern software engineering and delivery methodologies.
- Ability to operate effectively in ambiguous and evolving environments.
- Strong analytical and problem-solving skills with the ability to distinguish meaningful adoption from surface-level or self-reported adoption.
- Ability to quickly understand existing frameworks and contribute with minimal ramp-up time.
- Strong communication skills and the ability to work effectively with both technical teams and senior stakeholders.
Preferred Qualifications
- Experience with AI governance, auditability, responsible AI, or enterprise AI controls.
- Familiarity with AI catalogs, plugin ecosystems, and governed AI technology environments.
- Experience developing or evaluating technology maturity models, certification frameworks, or assessment methodologies.
- Experience working across large enterprises, multiple business units, or complex technology organizations.
- Experience with AI-assisted software engineering and developer productivity platforms.
- Strong facilitation and stakeholder management skills.
- Ability to challenge teams and validate evidence without creating a punitive or audit-focused environment.
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