Expert Engineer (Remote)
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Key skills for this role
About the Role
We are seeking an Expert Engineer on a contract basis to deploy and maintain AI-driven solutions for enterprise clients. The role involves integrating, optimizing, and troubleshooting AI models and cloud infrastructure, ensuring operational reliability.
Key Skills for This Role
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.
Requirements
- 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.
Full Job Posting
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.
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
- 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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