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- ### Design, develop, and deploy AI/ML, Generative AI, and intelligent automation solutions for engineering and business applications.
- ### Build enterprise AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and agentic AI frameworks.
- ### Develop AI-powered assistants, copilots, and workflow automation solutions.
- ### Evaluate and optimize AI models for accuracy, scalability, and production readiness.
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- ### Develop scalable backend services, APIs, and microservices using Python.
- ### Write clean, maintainable, and well-documented code following software engineering best practices.
- ### Participate in design reviews, code reviews, testing, and debugging activities.
- ### Contribute to reusable frameworks and shared AI components.
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- ### Develop and deploy AI applications on Azure, AWS, or Google Cloud platforms.
- ### Integrate AI services with enterprise applications and cloud-native solutions.
- ### Support containerization, orchestration, and CI/CD processes for AI workloads.
- ### Collaborate with MLOps teams to deploy, monitor, and maintain AI models.
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- ### Work with structured and unstructured data to support AI model development.
- ### Build and maintain data preparation and feature engineering pipelines.
- ### Support model monitoring, evaluation, and continuous improvement.
- ### Collaborate with data engineering teams to ensure high-quality data for AI applications.
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- ### Partner with product owners, architects, data engineers, and business teams to understand requirements and deliver AI solutions.
- ### Provide technical guidance to junior engineers and contribute to knowledge-sharing initiatives.
- ### Stay updated on emerging AI technologies, tools, and engineering best practices.
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- ### 15–20 years of experience in software engineering, AI/ML, or data engineering.
- ### Strong programming skills in Python and experience with object-oriented design principles.
- ### Hands-on experience with Machine Learning, Generative AI, and Large Language Models (LLMs).
- ### Experience with AI frameworks such as LangChain, LangGraph, Hugging Face, TensorFlow, or PyTorch.
- ### Knowledge of Retrieval-Augmented Generation (RAG), prompt engineering, and vector databases.
- ### Experience with Azure, AWS, or Google Cloud AI services.
- ### Familiarity with Docker, Kubernetes, REST APIs, Git, and CI/CD pipelines.
- ### Understanding of MLOps practices, model deployment, and AI lifecycle management.
- ### Strong analytical, problem-solving, and communication skills.
- ### Bachelor's or Master's degree in Computer Science, Engineering, Artificial Intelligence, Data Science, or a related field.
- ### We are committed to offering competitive benefits programs for all of our employees, and enhancing our programs when necessary.
- ### Have peace of mind and body with our health insurance
- ### Make yourself a priority with flexible schedules and leave Policy
- ### Drive forward your career through professional development opportunities Achieve your personal goals with our Employee Assistance Program.
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Carrier is An Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or veteran status, age or any other federally protected class.
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