AI/ML Architect/ Delivery Manager

The ideal candidate has progressed from software engineering, solution architecture, or technical leadership into delivery management or technology transformation. They must have personally contributed to building AI/ML solutions and successfully taken at least one AI-native solution into production, delivering measurable business value.

This is not a traditional project management or AI strategy role. You will work directly with VP-level and C-suite stakeholders, shape technical direction, guide engineering teams, and help the client scale AI from experimentation to production-grade, agent-driven software delivery.

Key Responsibilities

• AI Transformation: Advise client leadership on AI adoption and define AI-enabled Software Development Lifecycle (AI SDLC) practices, including engineering workflows, tooling, governance, and operating models.
• AI Architecture & Solution Delivery: Guide solution architecture, shared AI infrastructure, technology roadmaps, and the implementation of scalable AI/ML and agentic AI solutions.
• Production AI Delivery: Lead initiatives from discovery and solution design through implementation, production rollout, and value realization.
• AI Governance: Establish frameworks for AI agent orchestration, human-in-the-loop oversight, auditability, traceability, and responsible AI adoption in an enterprise environment.
• Executive Client Advisory: Engage directly with VP-level and C-suite stakeholders, challenge assumptions constructively, translate complex technical concepts into business outcomes, and influence strategic decisions.
• Delivery Leadership: Own delivery planning, roadmaps, dependencies, risks, escalations, governance, and execution across multiple AI initiatives.
• Consulting & Account Growth: Support solution shaping, pre-sales discussions, delivery proposals, and identification of opportunities to expand the client engagement.
• Continuous Innovation: Evaluate emerging AI engineering practices, improve delivery effectiveness, and champion new approaches to AI-enabled software development.

Required Qualifications

• Strong technical foundation in Computer Science, Software Engineering, or a related engineering discipline, with experience in software development and solution/enterprise architecture.
• Proven delivery leadership across complex technology programs, ideally in a consulting or systems integration environment.
• Demonstrated experience building and delivering at least one AI-native or AI/ML solution into production, with measurable business or engineering benefits.
• Strong understanding of AI/ML architecture, Generative AI, agentic AI, and enterprise AI implementation challenges.
• Practical understanding of the AI SDLC, including AI-assisted engineering, evaluation, deployment, governance, and production adoption.
• Ability to discuss technical designs, implementation decisions, engineering trade-offs, and production challenges credibly with senior engineers and architects.
• Experience working directly with business stakeholders and advising VP-level or C-suite leaders.
• Strong consulting mindset, executive communication, problem-solving, and organizational change leadership skills.
• Experience with a major systems integrator, Big Four consultancy, Accenture, EPAM, or a comparable consulting organization.