Note: The job is a remote job and is open to candidates in USA. Dice is seeking an Agentic AI Forward Deployed Engineer / Architect to design and develop AI/ML applications. The role requires strong programming skills in Python and experience in implementing scalable AI/ML solutions, with a focus on hands-on coding and architecture.

Responsibilities

• Minimum 6+ years (not more than 15+ years overall) of experience in designing and development of AI/ML applications
• Strong handson programming experience (Python required) with the ability to design and implement productionready solutions (experience in JS/NodeJS or .NET/C# is a plus)
• Architecture and systemdesign experience, with a proven track record of translating designs into working code (must still code 50 70% of the time)
• Practical experience implementing AI/ML solutions endtoend, including data preparation, model usage, and integration into applications (using frameworks like ScikitLearn, TensorFlow, or PyTorch)
• Experience designing and building scalable ML/AI systems using APIs, microservices, and eventdriven patterns with direct handson implementation responsibility
• Strong data handling skills, including Pandas/NumPy and working with structured and unstructured data in real systems
• Cloudnative experience (Azure/AWS) with handson deployment, debugging, and performance tuning of AI workloads
• Solid software engineering and DevOps practices, including Git, CI/CD pipelines, logging, monitoring, and production readiness
• Individual contributor role no people management; must personally design, code, debug, and support solutions

Skills

• Minimum 6+ years (not more than 15+ years overall) of experience in designing and development of AI/ML applications
• Strong handson programming experience (Python required) with the ability to design and implement productionready solutions (experience in JS/NodeJS or .NET/C# is a plus)
• Architecture and systemdesign experience, with a proven track record of translating designs into working code (must still code 50 70% of the time)
• Practical experience implementing AI/ML solutions endtoend, including data preparation, model usage, and integration into applications (using frameworks like ScikitLearn, TensorFlow, or PyTorch)
• Experience designing and building scalable ML/AI systems using APIs, microservices, and eventdriven patterns with direct handson implementation responsibility
• Strong data handling skills, including Pandas/NumPy and working with structured and unstructured data in real systems
• Cloudnative experience (Azure/AWS) with handson deployment, debugging, and performance tuning of AI workloads
• Solid software engineering and DevOps practices, including Git, CI/CD pipelines, logging, monitoring, and production readiness
• Individual contributor role no people management; must personally design, code, debug, and support solutions

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