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Mid-level AI title, metro location, and recognizable employer increase applicant competition but role is specialized.
Core ML and MLOps skills transfer across industries, though healthcare domain experience is advantageous.
Requires proven production AI deployments, cloud and ML framework expertise, making screening stringent.
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Design, build, and deploy Agentic AI frameworks enabling autonomous decision-making and task execution.
Own the end-to-end lifecycle of AI solutions including data preparation, model training, evaluation, deployment, and monitoring.
Develop Cognitive Automation and Generative AI applications integrated into production environments ensuring scalability and reliability.
Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
Proven experience deploying Agentic AI solutions in production environments.
Strong programming skills in Python; proficiency in SQL and software engineering principles (DSA, design patterns, SOLID).
Experience with cloud platforms (preferably Azure) and familiarity with machine learning frameworks (PyTorch, TensorFlow, Scikit-learn).
Experienced in full-stack AI engineering with a strong software engineering foundation and practical AI deployment expertise.
Capable of integrating complex AI models into scalable, maintainable production systems within cross-functional teams.
Knowledgeable in emerging AI techniques including reinforcement learning, generative models, and MLOps practices for CI/CD of AI models.