AI Solution Delivery Lead

Job Summary

We are seeking an AI Solution Delivery Lead to drive the end-to-end delivery of AI, Machine Learning, Generative AI, and intelligent automation solutions, from requirements and solution design through production deployment.

The role combines AI expertise, solution delivery, and stakeholder leadership to deliver scalable, secure, high-quality solutions aligned with business objectives and measurable outcomes.

Key Responsibilities

1. AI Solution Delivery

• Lead end-to-end delivery of AI, ML, Generative AI, and intelligent automation solutions from requirements through production.
• Coordinate delivery across AI, data, software, cloud, and infrastructure teams to meet scope, timelines, quality, and business objectives.
• Ensure successful production deployment, operational transition, and ongoing solution performance.

2. Solution Design & Architecture

• Translate business requirements into scalable, secure, and fit-for-purpose AI solutions.
• Collaborate with architects, data scientists, AI engineers, developers, and cloud teams to define solution architecture and integrations.
• Evaluate and recommend appropriate AI models, platforms, frameworks, and technologies.

3. Project & Delivery Management

• Manage scope, timelines, resources, risks, dependencies, and deliverables across AI initiatives.
• Define delivery plans, milestones, success criteria, and resource requirements.
• Apply Agile/Scrum practices and proactively manage risks, issues, and changes.

4. Stakeholder Management

• Partner with business and technology stakeholders to understand requirements, priorities, and expected outcomes.
• Communicate solution approaches, delivery progress, risks, and key decisions effectively.
• Facilitate requirements workshops, solution reviews, demonstrations, and delivery discussions.

5. AI Technology & Innovation

• Evaluate and apply emerging technologies including Generative AI, LLMs, RAG, AI Agents, Copilots, and intelligent automation.
• Identify opportunities to leverage AI to improve business processes, efficiency, and outcomes.
• Promote reusable AI capabilities, accelerators, and best practices across initiatives.

6. Governance, Quality & Continuous Improvement

• Ensure AI solutions meet requirements for security, privacy, responsible AI, performance, reliability, and compliance.
• Establish appropriate testing, validation, documentation, monitoring, and lifecycle management practices.
• Drive continuous improvement through quality reviews, lessons learned, and delivery optimization.

Required Qualifications & Experience

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, Information Technology, or a related field.
• 8+ years of experience in IT/software, technology delivery, digital transformation, or related fields, including at least 2 years of hands-on experience delivering AI/ML or Generative AI solutions.
• Proven experience delivering AI, Machine Learning, Generative AI, or intelligent automation solutions from concept through production.
• Strong understanding of enterprise technology, cloud platforms, data, system integration, and AI solution architecture.
• Proven experience leading cross-functional technical teams and complex technology initiatives.
• Excellent project management, stakeholder management, communication, analytical, problem-solving, and decision-making skills.

Technical Skills

• AI, ML & Generative AI: AI/ML, LLMs, NLP, Computer Vision, Generative AI, RAG, AI Agents, Copilots, prompt engineering, and model evaluation.
• AI Architecture & Integration: AI solution architecture, APIs, data pipelines, enterprise integration, AI platforms, and production AI environments.
• Cloud, Data & AI Platforms: Experience with enterprise cloud and AI platforms such as Azure/Azure AI/Azure OpenAI, AWS AI/ML, or Google Cloud AI, along with Python, REST APIs, vector databases, semantic search, and modern data platforms.
• MLOps, LLMOps & DevOps: Model deployment, CI/CD, Docker, Kubernetes, monitoring, model lifecycle management, MLOps, LLMOps, and AI productionization.
• AI Security & Governance: AI security, data privacy, responsible AI, model governance, risk management, compliance, and enterprise AI controls.

What We Offer

• Opportunity to work on AI, Generative AI, Agentic AI, and emerging technologies across real-world business use cases.
• Exposure to innovative AI and digital transformation initiatives across diverse business challenges.
• A collaborative, technology-driven environment working with multidisciplinary AI and technology teams.
• Opportunities for professional growth, continuous learning, and development in rapidly evolving AI technologies.
• Opportunity to shape and deliver impactful AI solutions while contributing to reusable capabilities and accelerators.

Work Location: In person