AI Engineer
First seen by Alion on Sep 25, 2026.
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.
Skills
Artificial Intelligence, Node.js, Tensorflow, PyTorch, AWS, Microservices Architecture, MLOps, Machine Learning