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Tier-1 brand, metro location, mid-level generalist AI role with broad full-stack and MLOps requirements.
Role requires deep ML/Generative AI and MLOps expertise, limiting cross-industry transferability.
Explicit 6-9 years plus 3-4 years AI and mandatory ML, cloud, MLOps, and DevOps skills.
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Design and implement end-to-end AI architectures including data, model, application, and infrastructure layers for enterprise scale.
Develop and deploy AI solutions involving machine learning, generative AI, and integration with enterprise platforms and automation workflows.
Lead technical teams by providing AI architecture guidance, enable MLOps practices, and ensure AI systems' scalability, security, and compliance.
6 to 9 years of overall IT experience with 3-4 years hands-on in AI, Machine Learning, or Generative AI solutions.
Bachelor’s Degree in Engineering (Computer Science or Information Technology) or equivalent 100% relevant professional experience.
Technical skills in full stack backend development (Python, Java, .NET, or Node.js), AI/ML frameworks (TensorFlow, PyTorch, etc.), cloud platforms (Azure, AWS, GCP), and container orchestration technologies (Docker, Kubernetes).
Experience implementing AI system architecture, MLOps pipelines, CI/CD, and integration with enterprise APIs and microservices.
Experienced full stack engineer and AI architect capable of translating business problems into scalable AI solutions and deployment strategies.
Familiar with generative AI including LLMs, prompt engineering, and MLOps to support real-time and batch AI production environments.
Able to provide technical leadership and mentorship, collaborate across product and business teams, and work in complex enterprise technology environments.