Job Purpose
- Architect and maintain cloud-native infrastructure on AWS, Azure, or GCP.
- Develop and integrate AI/ML models into client-facing SaaS products.
- Collaborate with cross-functional teams to deliver intelligent, scalable systems.
Key Responsibilities
- Design, deploy, and manage cloud infrastructure using IaC tools (Terraform, CDK).
- Build and integrate AI/ML pipelines for automation and data intelligence.
- Optimize cloud costs, performance, and security posture.
- Develop APIs and microservices that expose AI capabilities to applications.
- Monitor cloud environments and implement observability best practices.
- Collaborate with security teams to ensure compliance and hardening.
Minimum Requirements
- Bachelor's degree in Computer Science, Engineering, or related field.
- 1–3 years of hands-on experience with cloud platforms (AWS preferred).
- Proficiency in Python and at least one cloud SDK.
- Understanding of containerization (Docker, Kubernetes).
- Familiarity with ML frameworks such as TensorFlow, PyTorch, or scikit-learn.
Preferred Competencies
- Certifications: AWS Solutions Architect, Google Cloud Professional, or equivalent.
- Experience with LLM APIs (OpenAI, Bedrock, Vertex AI).
- Knowledge of CI/CD pipelines and DevSecOps practices.
- Strong problem-solving skills and a bias for automation.
- Ability to work independently and manage multiple priorities.
Interested in this role?
Submit your application — we review every one carefully.
