Job Overview:

We are seeking a highly experienced Automation Platform Engineering Specialist to lead the operationalization and stability of our enterprise infrastructure and API platforms, with a strong focus on AI/ML integration. The ideal candidate will have extensive experience in infrastructure automation, containerization, configuration management, high-availability deployment, and bringing AI/ML solutions into production. In this role, you will be instrumental in ensuring our CI/CD pipelines are robust and secure, driving architectural strategy, and leading complex troubleshooting efforts across multi-region environments, while also overseeing the operationalization of AI/ML models.

Key Responsibilities:

DevOps & Infrastructure Automation:

• Troubleshoot and expertly resolve complex production issues related to APIs, automation platforms, and promotion pipelines, ensuring minimal downtime.
• Drive continuous integration/continuous delivery (CI/CD) pipelines for efficient and reliable application, API, and AI/ML model deployments.
• Operationalize and maintain highly available services deployed across multi-region and multi-data center environments.
• Lead efforts in handling outages, performing thorough root cause analysis, and providing sound architectural recommendations for future prevention.
• Assess the current technological landscape to identify key areas for infrastructure automation, configuration management, monitoring, and alerting.

AI/ML Operationalization & Governance:

• Collaborate with AI/ML teams to ensure the platform effectively supports the deployment and operationalization of AI/ML solutions.
• Ensure that AI/ML models can be seamlessly integrated and deployed into production, focusing on platform scalability, performance, and reliability.
• Support the integration of AI/ML artifacts into CI/CD pipelines for automated deployment and ongoing maintenance.
• Contribute to ensuring robust platform governance and operational stability for AI/ML applications.

Security Leadership:

• Implement robust security best practices throughout the entire CI/CD pipeline and infrastructure, with a specific focus on securing AI/ML workloads.
• Conduct regular security audits and vulnerability assessments to identify and mitigate risks.
• Develop and enforce security policies and standards across the platform.
• Lead security incident response efforts, ensuring rapid and effective resolution.

Technical Leadership & Mentorship:

• Provide clear technical guidance and mentorship to junior developers, fostering a culture of technical excellence.
• Actively participate in code reviews, architectural discussions, and contribute significantly to the overall technical strategy, particularly concerning automation and AI/ML infrastructure.
• Demonstrate effective cross-functional project, resource, and stakeholder management, including engaging with internal audit and external regulators.
• Manage vendor interactions for troubleshooting, enhancement requests, and guiding vendor roadmaps to meet internal standards.

Required Technical Skills & Expertise:

• Experience: 8+ years of relevant experience in software engineering and platform operations, including significant AI/ML operationalization.
• Containerization & PaaS: Strong experience with containerization technologies (Docker, Kubernetes) and deep expertise in platforms like OpenShift.
• Automation & IaC: Experience with Infrastructure as Code (IaC) and CI/CD tooling (e.g., Ansible, Chef, Groovy, Terraform, Jenkins, Harness).
• API & Microservices: Expertise in REST API development, microservice architectures, and managing highly available platforms supporting various workloads.
• OS & Scripting: In-depth knowledge of Linux platforms (installation, configuration, advanced troubleshooting) and strong scripting skills (e.g., Shell, Ansible Playbook, Chef cookbook, Python, Ruby).
• Cloud Platforms: Hands-on experience with virtualization and cloud technologies (e.g., GCP, AWS).
• Observability: Proficiency in gathering performance metrics, troubleshooting, tuning, and monitoring complex systems using solutions like Grafana, Prometheus, Kibana, and Splunk.
• AI/ML Operationalization: Demonstrated experience in deploying and managing AI/ML applications in production environments, specifically focusing on MLOps, automated deployment, monitoring, and governance of models.

Preferred Qualifications:

• Basic knowledge of advanced DevOps pipeline principles and practices.
• Deep understanding of security concepts and best practices in software development and infrastructure.
• Certifications: Relevant certifications such as Red Hat Certified Engineer (RHCE), Certified Kubernetes Administrator (CKA), AWS Certified DevOps Engineer, or Google Cloud Professional DevOps Engineer are highly preferred. Specific certifications demonstrating expertise in cloud platforms (e.g., AWS Advanced Networking, Azure Solutions Architect Expert), security (e.g., Certified Information Systems Security Professional - CISSP), or AI/ML (e.g., AWS Certified Machine Learning Specialty, Google Cloud Professional Machine Learning Engineer) are highly advantageous.

Personal Attributes:

• Highly motivated, self-directed, and detail-oriented.
• Strong analytical and complex problem-solving skills.
• Excellent written and verbal communication skills, with the ability to explain technical concepts to both technical and executive audiences.
• Ability to work effectively under pressure and manage competing deadlines or unexpected changes in requirements

Education: Bachelor's degree in Computer Science or related field, or equivalent practical experience.