We are seeking an Expert Engineer to deploy and maintain AI-driven solutions for enterprise clients. The successful candidate will work directly with customers to integrate, optimize, and troubleshoot AI models and cloud infrastructure. The role requires a strong technical background, excellent debugging skills, and the ability to articulate technical concepts to non-technical stakeholders.
Key Highlights
Key Responsibilities
Technical Skills Required
Benefits & Perks
Job Description
- Role: Expert Engineer (Remote)
- Location: Remote (Work from Anywhere)
- Payout: Competitive, based on experience
Role Overview:
This contractual role focuses on deploying and maintaining AI-driven solutions for enterprise clients in real-world environments. You will work directly with customers to integrate, optimize, and troubleshoot AI models and cloud infrastructure, ensuring operational reliability and performance. The work supports scalable AI adoption across industries transitioning to intelligent automation. Precision in deployment and hands-on technical support are central to success.
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Key Responsibilities:
• Deploy AI models and cloud-based inference systems into customer environments with minimal latency and maximal uptime.
• Conduct technical onboarding sessions and provide live debugging support during integration to resolve real-time issues.
• Monitor system performance using SLA dashboards and recommend infrastructure adjustments to meet service-level targets.
• Write and maintain deployment documentation, including runbooks and troubleshooting guides for internal and customer teams.
• Collaborate with product and engineering teams to relay field feedback and influence roadmap priorities.
Required Skills & Qualifications:
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• Bachelor’s degree in computer science, engineering, or a related quantitative field with 3+ years of hands-on experience deploying AI systems.
• Proficiency in Python and at least one infrastructure-as-code tool such as Terraform or Ansible for reproducible deployments.
• Experience with cloud platforms (e.g., AWS, GCP, or Azure) and container orchestration (e.g., Kubernetes) in production settings.
• Strong debugging skills across distributed systems, including logs, metrics, and network diagnostics.
• Ability to articulate technical concepts to non-technical stakeholders and document complex procedures clearly.
More About the Opportunity:
This role offers the chance to influence how global organizations operationalize AI at scale, directly impacting their ability to deliver intelligent products. You will gain exposure to cutting-edge AI deployments across multiple sectors while shaping best practices in reliability and performance. The position also provides flexibility to work from anywhere with a results-driven contract structure.
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