AI Engineer

Key Responsibilities :

- Architect AI Solutions : Design scalable AI/ML systems leveraging modern frameworks (TensorFlow, PyTorch, Hugging Face, etc.).

- Backend Development : Lead backend solution design and development using Node.js, ensuring performance, security, and maintainability.

- Cloud Integration : Define and implement cloud-native architectures on AWS, including compute, storage, and AI/ML services.

- Technical Leadership : Guide engineering teams on best practices, code reviews, and architectural decisions.

- Innovation & Strategy : Evaluate emerging AI technologies and frameworks to recommend adoption strategies.

- Collaboration : Work closely with product managers, data scientists, and DevOps teams to deliver end-to-end AI solutions.

Required Skills :

- Experience : 4 - 6 years in software engineering, with at least 2 - 4 years in AI/ML solution architecture.

- AI/ML Frameworks : Proficiency in TensorFlow, PyTorch, Scikit-learn, Hugging Face, or similar.

- Backend Development : Strong expertise in Node.js, RESTful APIs, and microservices architecture.

- Cloud Awareness : Hands-on experience with AWS services (SageMaker, Lambda, EC2, S3, CloudFormation).

- Architecture & Design : Proven ability to design scalable, secure, and high-performance systems.

Desired Skills :

- Exposure to MLOps practices (CI/CD for ML, model deployment pipelines).

- Knowledge of data engineering concepts (ETL, data lakes, streaming).

- Experience with containerization (Docker, Kubernetes).

- Familiarity with security best practices in AI and cloud environments.

Soft Skills :

- Strong communication, leadership, and problem-solving abilities.