Chief AI Architect

10 hours ago

Thāne, Maharashtra, India beBeeIntegration Full time ₹ 60,00,000 - ₹ 1,20,00,000
AI Integration Engineer

We are seeking a skilled and detail-oriented AI integration professional to join our team in Ahmedabad. In this role, you will be responsible for deploying and integrating AI/ML models into production environments, ensuring their scalability, reliability, and security.

You will work closely with data scientists, software engineers, DevOps, and product teams to streamline AI adoption and ensure maximum impact from our AI-driven solutions.

Key Responsibilities:

  • Deploy and integrate AI models: Collaborate with AI/ML teams to deploy machine learning models into applications and services.
  • Build APIs and microservices: Design and implement APIs, SDKs, and microservices that enable seamless AI model consumption.
  • Ensure reliability: Maintain high availability, scalability, and security of AI services in production.
  • Monitor and maintain models: Implement CI/CD pipelines, observability tools, and monitoring systems to track and improve model performance.
  • Automate workflows: Build automated pipelines for model retraining, versioning, and rollback.
  • Optimize performance: Implement caching strategies, model compression, and other techniques to improve inference speed and system efficiency.
  • Cloud and hybrid infrastructure: Work with AWS, GCP, or Azure environments and support hybrid setups (cloud + on-prem).
  • Collaborate cross-functionally: Partner with DevOps, software engineers, and product teams to integrate AI capabilities smoothly into products and services.

Required Skills and Qualifications:

  • Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
  • 3-6 years of experience in software engineering, backend development, or MLOps.
  • Strong proficiency in Python with experience using FastAPI, Flask, or Django.
  • Experience integrating ML models with tools like TensorFlow Serving, TorchServe, ONNX, or custom model wrappers.
  • Hands-on experience with Docker, Kubernetes, and container orchestration.
  • Understanding of CI/CD pipelines, MLOps practices, and model lifecycle management.
  • Familiarity with cloud platforms (AWS, GCP, Azure) and their AI/ML services.
  • Excellent English communication skills – ability to work with cross-functional teams and present technical solutions clearly.

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