Technical Project Manager
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Key skills for this role
About the Role
AceNet seeks a Technical Project Manager with 5-8 years of experience and a strong AI/ML background to lead delivery of AI solutions for enterprise customers. The role combines project management with technical expertise in RAG, generative AI, and LLMs.
Key Skills for This Role
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
Requirements
- 5–8 years of overall experience, including as a Technical Project Manager or similar role
- Strong hands on background in AI and ML development
- Good understanding of Generative AI, LLMs, and RAG architectures
- Experience managing AI/ML product development and deployment projects
- Knowledge of AI/ML frameworks such as Python, TensorFlow, PyTorch, LangChain, LlamaIndex, Vector Databases
- Experience working in Agile/Scrum environments
- Excellent project planning, risk management, and stakeholder management skills
- Strong customer facing and consulting experience
Full Job Posting
About the Role
- We are seeking an experienced Technical Project Manager with a strong background in AI/ML development to lead the delivery of cutting edge AI solutions for enterprise customers.
- The ideal candidate will combine technical expertise in AI/ML technologies, including Retrieval Augmented Generation (RAG), with strong project management and stakeholder management skills.
- This is a customer facing role requiring the ability to engage with business and technical stakeholders.
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.
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.
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.
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