AI Solution Delivery Lead

Role summary

Delivery and architecture

• Lead AI solution delivery and coordinate AI, data, software, cloud, and infrastructure teams against scope, timelines, quality, and business goals.
• Ensure production deployment, operational transition, and ongoing performance.
• Translate business requirements into scalable, secure solutions; work with technical specialists to define architectures and integrations.
• Evaluate and recommend AI models, platforms, frameworks, and technologies.
• Manage scope, timelines, resources, risks, dependencies, deliverables, plans, milestones, success criteria, and resource requirements.
• Apply Agile/Scrum and proactively manage risks, issues, and changes.

Stakeholders, innovation, and governance

• Partner with business and technology stakeholders; communicate approaches, progress, risks, and decisions; facilitate workshops, reviews, demonstrations, and delivery discussions.
• Evaluate emerging technologies including generative AI, LLMs, RAG, AI agents, copilots, and intelligent automation; identify opportunities to improve business processes and outcomes.
• Promote reusable AI capabilities, accelerators, and best practices.
• Ensure security, privacy, responsible AI, performance, reliability, and compliance; establish testing, validation, documentation, monitoring, and lifecycle practices.
• Drive continuous improvement through quality reviews, lessons learned, and delivery optimization.

Qualifications and experience

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, Information Technology, or a related field.
• 8+ years in IT/software, technology delivery, digital transformation, or related fields, including at least 2 years hands-on delivering AI/ML or generative AI solutions.
• Proven delivery of 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.
• Experience leading cross-functional technical teams and complex technology initiatives.
• Strong project management, stakeholder management, communication, analytical, problem-solving, and decision-making skills.

Technical skills

• AI/ML, LLMs, NLP, computer vision, generative AI, RAG, AI agents, copilots, prompt engineering, and model evaluation.
• AI architecture and integration, APIs, data pipelines, enterprise integration, AI platforms, and production AI environments.
• Enterprise cloud and AI platforms such as Azure/Azure AI/Azure OpenAI, AWS AI/ML, or Google Cloud AI; Python, REST APIs, vector databases, semantic search, and modern data platforms.
• Model deployment, CI/CD, Docker, Kubernetes, monitoring, model lifecycle management, MLOps, LLMOps, and AI productionization.
• AI security, data privacy, responsible AI, model governance, risk management, compliance, and enterprise AI controls.

What the employer offers

• Work on real-world AI, generative AI, agentic AI, and emerging technology use cases.
• Exposure to AI and digital transformation initiatives across business challenges, with multidisciplinary teams.
• Professional growth and continuous learning, and the opportunity to shape impactful solutions and reusable capabilities.

Work location

• Work location is in person.