AI Automations Cloud Deployment Engineer (Remote - US)

This position is posted by Jobgether on behalf of a partner company. We are currently looking for an AI Automations Cloud Deployment Engineer in the United States.

As an AI Automations Cloud Deployment Engineer, you will lead the end-to-end design, deployment, and optimization of AI and machine learning solutions across major cloud platforms. You will build scalable, secure infrastructures that power intelligent systems and advanced analytics within a global organization. Working closely with cross-functional teams, you will ensure AI models are seamlessly deployed and maintained for real-world performance and impact. This position offers the opportunity to work with cutting-edge cloud and AI technologies, contributing to large-scale innovation in a highly technical and mission-driven environment.

Accountabilities:

• Design, implement, and manage cloud-based infrastructures to support AI and machine learning workloads on platforms such as AWS, Azure, or GCP.
• Develop and optimize MLOps pipelines for model training, testing, deployment, and continuous monitoring.
• Apply best practices in cloud architecture to achieve scalability, reliability, and cost efficiency while maintaining strong security and compliance standards.
• Collaborate with data scientists, engineers, and architecture teams to deploy AI models and integrate them within enterprise systems.
• Use containerization (Docker) and orchestration (Kubernetes) technologies to streamline deployment and scaling of AI applications.
• Explore and integrate emerging technologies such as generative AI, LLMs, and retrieval-augmented generation (RAG) to enhance automation capabilities.
• Provide technical leadership, guidance, and stakeholder engagement throughout project delivery cycles.

Requirements

• Bachelor’s degree in Computer Science, Engineering, or a related field, with 10+ years of experience in AI, ML, or cloud solution engineering.
• Strong background in MLOps tools, principles, and lifecycle management.
• Professional certification in AWS or Azure (AI/ML specialization preferred).
• Proficiency in Python, Java, or C++, and familiarity with Terraform or CloudFormation.
• Hands-on experience with containerization (Docker) and orchestration (Kubernetes).
• Exposure to generative and agentic AI frameworks.
• Strong communication, collaboration, and analytical problem-solving skills.
• Master’s degree or SAFe DevOps certification is a plus.
• Candidates must meet U.S. Person eligibility requirements.

Benefits

• Competitive salary range between USD 124,000 – 250,000, based on experience and qualifications.
• Comprehensive health, dental, and vision coverage.
• 401(k) retirement plan with company match.
• Flexible work schedules and remote-first setup.
• Paid parental leave (including paternal) and backup care options.
• Educational assistance and professional development support.
• Achievement awards and recognition programs.
• Inclusive work environment supporting equal opportunities for all applicants.

Jobgether is a Talent Matching Platform that partners with companies worldwide to efficiently connect top talent with the right opportunities through AI-driven job matching.

When you apply, your profile goes through our AI-powered screening process designed to identify top talent efficiently and fairly.
🔍 Our AI evaluates your CV and LinkedIn profile thoroughly, analyzing your skills, experience, and achievements.
📊 It compares your profile to the job’s core requirements and success indicators to determine your match score.
🎯 Based on this analysis, we automatically shortlist the top 3 candidates who best fit the role.
🧠 When necessary, our human team conducts an additional manual review to ensure no exceptional profile is overlooked.

The process is transparent, skills-based, and bias-free — focused entirely on your fit for the role. Once the shortlist is completed, it is shared directly with the company owning the job opening. The final decision and next steps (such as interviews or further assessments) are handled by their internal hiring team.

Thank you for your interest!

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