AI Project Manager / Platform Delivery Manager
Deliver AI platform implementations, manage cross-functional teams, and ensure regulatory compliance. Strong knowledge of GxP and SOX compliance frameworks is required. Excellent stakeholder management skills and experience with AI platform delivery are essential.
Key Highlights
Key Responsibilities
Technical Skills Required
Benefits & Perks
Nice to Have
Job Description
1️⃣ AI Project Manager / Platform Delivery Manager
US – Fully remote
Project till end of 2026
📍 Role Overview
The AI Project Manager / Platform Delivery Manager is responsible for end-to-end coordination and successful delivery of AI platform implementations, including pilot, MVP, and scaled production deployments. The role ensures projects are delivered on time, within scope, and aligned with regulatory and compliance standards (GxP, SOX).
🎯 Key Responsibilities
- Lead end-to-end delivery of AI platform projects
- Develop and manage detailed project plans
- Coordinate cross-functional teams (engineering, data, business stakeholders)
- Schedule and facilitate discovery workshops and stakeholder sessions
- Manage risk, scope, budget, and timeline
- Oversee GxP and SOX qualification and validation activities
- Ensure proper documentation and compliance standards are met
- Provide executive-level status reporting
🧠 Required Skills & Experience
- Proven experience delivering enterprise software or AI platform implementations
- Experience with AI platform delivery (strongly preferred)
- Strong knowledge of GxP and SOX compliance frameworks
- Experience in regulated industries (pharma, biotech, finance, utilities preferred)
- Excellent stakeholder management skills
- Agile / Scrum methodology experience
- Familiarity with cloud environments (AWS, Azure, GCP)
2️⃣ AI Platform Specialist / Application Engineer
US – fully remote
Project till end of the year
📍 Role Overview
The AI Platform Specialist / App Engineer is responsible for configuring, setting up, and deploying AI modules and applications across pilot, MVP, and scaled environments. This role ensures proper configuration of workflows, data models, and user access structures.
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🎯 Key Responsibilities
- Configure AI platform modules and applications
- Setup workflows and data pipelines for pilots and MVPs
- Support scaling solutions to production environments
- Configure user roles, permissions, and security settings
- Support training sessions and user onboarding
- Collaborate with developers and data engineers
- Assist in testing and validation activities
🧠 Required Skills & Experience
- Hands-on experience with C3 AI Suite configuration
- Experience configuring enterprise applications
- Understanding of data models and integration concepts
- Familiarity with cloud platforms
- Knowledge of DevOps processes (CI/CD pipelines preferred)
- Strong troubleshooting and problem-solving skills
3️⃣ AI Engineer / Developer
US– fully remote
Project till end of 2026
📍 Role Overview
The AI Engineer / Developer is responsible for platform development and integration of AI applications with client systems, including ERP, CRM, IoT, and data warehouses.
🎯 Key Responsibilities
- Develop and customize applications within the AI platform
- Integrate AI with enterprise systems (SAP, Salesforce, etc.)
- Build APIs and data ingestion pipelines
- Implement machine learning models within the C3 framework
- Support data mapping and transformation
- Collaborate with data scientists and platform architects
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🧠 Required Skills & Experience
- Strong hands-on development experience in AI
- Proficiency in Java and/or Python
- Experience with REST APIs and system integrations
- Experience integrating enterprise systems
- Strong understanding of data engineering concepts
- Familiarity with cloud-native architectures
4️⃣ Platform Support Engineer
US – fully remote
Project till end of 2026
📍 Role Overview
The Platform Support Engineer provides operational and technical support for deployed AI applications and scaled production environments. The role ensures stability, performance, and issue resolution post-deployment.
🎯 Key Responsibilities
- Monitor and support deployed AI applications
- Troubleshoot platform and integration issues
- Manage incident resolution and root cause analysis
- Support performance optimization
- Coordinate with development teams for bug fixes
- Maintain documentation and knowledge base
- Support upgrades and patch management
🧠 Required Skills & Experience
- Experience supporting enterprise platforms (AI preferred)
- Strong troubleshooting and debugging skills
- Understanding of cloud infrastructure
- Familiarity with monitoring tools and incident management processes
- Basic knowledge of APIs and data flows
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