Project Manager / Scrum Master / AI Lead

Role Overview

Project Management

Key Responsibilities

Project Management

• Lead planning, execution, monitoring, and delivery of technology projects.
• Define project scope, timelines, budgets, and deliverables.
• Manage cross-functional teams and vendor partners.
• Track risks, issues, and dependencies with proactive mitigation.
• Provide clear and regular updates to stakeholders and senior leadership.
• Ensure adherence to quality standards and governance frameworks.
  

Scrum & Agile Delivery

• Facilitate Agile ceremonies: daily stand-ups, sprint planning, reviews, and retrospectives.
• Work closely with Product Owners to maintain a prioritized backlog.
• Remove impediments and foster a culture of continuous improvement.
• Coach teams on Agile principles and improve delivery velocity.
• Ensure transparency using Agile tools such as JIRA or Azure DevOps.
  

AI/ML & Generative AI Leadership

• Lead design, development, and deployment of AI/ML and Generative AI solutions.
• Architect and implement models including LLMs, embeddings, RAG, and transformers.
• Drive AI strategy, roadmap, POCs, and production-grade implementations.
• Work with data engineering teams on data pipelines, model training, and MLOps workflows.
• Ensure responsible AI practices, security, and compliance in model usage.
• Mentor AI engineers, data scientists, and technical teams.
  

Required Skills & Experience

• 715 years of experience in IT, with exposure across Project Management, Agile delivery, and AI/ML initiatives.
• Strong understanding of SDLC, Agile, Scrum, and DevOps practices.
• Hands-on experience with AI/ML frameworks (TensorFlow, PyTorch), Python, and cloud platforms (AWS/Azure/GCP).
• Experience working with LLMs, Generative AI models, prompt engineering, and vector databases.
• Excellent communication, stakeholder management, and leadership skills.
• Certifications such as PMP, PRINCE2, CSM/PSM, or AI/ML-related credentials are a strong advantage.
  

Preferred Qualifications

• Experience delivering enterprise-scale automation, analytics, or AI/ML programs.
• Exposure to cloud-native architectures and MLOps pipelines.
• Ability to oversee both technical and non-technical project streams.