Technical Project Manager

About the Role

Technical Project Manager

Retrieval-Augmented Generation (RAG)

Key Responsibilities

• Lead end-to-end delivery of AI/ML projects from requirements gathering through deployment and post-production support.
• Manage project scope, timelines, risks, dependencies, and resource allocation.
• Work closely with AI/ML engineers, data scientists, architects, and product teams to deliver scalable AI solutions.
• Drive customer discussions, understand business requirements, and translate them into technical deliverables.
• Facilitate project planning, sprint reviews, status reporting, and stakeholder communication.
• Monitor project progress and ensure alignment with quality, budget, and timeline expectations.
• Provide technical guidance and oversight on AI/ML solution design and implementation.
• Collaborate with customers to define use cases, success metrics, and deployment strategies.
• Identify project risks and proactively develop mitigation plans.
• Stay updated on emerging AI technologies and industry best practices.

Required Skills & Qualifications

• 5–8 years of overall experience, including experience as a Technical Project Manager or similar role.
• Strong hands-on background in Artificial Intelligence (AI) and Machine Learning (ML) development.
• Good understanding of Generative AI, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG) architectures.
• Experience managing AI/ML product development and deployment projects.
• Knowledge of AI/ML frameworks and tools such as Python, TensorFlow, PyTorch, LangChain, LlamaIndex, Vector Databases, or similar technologies.
• Experience working in Agile/Scrum environments.
• Excellent project planning, risk management, and stakeholder management skills.
• Strong customer-facing and consulting experience.
• Exceptional verbal and written communication skills.
• Ability to bridge business requirements and technical implementation.

Preferred Qualifications

• Experience delivering GenAI solutions in enterprise environments.
• Exposure to cloud platforms such as AWS, Azure, or Google Cloud.
• Project Management certifications such as PMP, PRINCE2, Scrum Master, or Agile certifications.
• Experience with AI solution architecture and deployment strategies.

Key Competencies

• Technical Leadership

• Risk & Dependency Management

• Nice to Have
• Experience with MLOps, model deployment, and monitoring.
• Exposure to prompt engineering, vector search, embeddings, and AI agent frameworks.
• Experience working with global customers and distributed teams.