Production Support Engineer

ASM Tech Solutions; Town of Florida (NY); Hybrid; USD 90,000 - 120,000; Full time

Job summary

ASM Tech Solutions seeks a Level 2 production support engineer to monitor, troubleshoot, and resolve incidents across AI platforms, cloud infrastructure, data pipelines, and model-serving environments.

You will deploy, orchestrate, and manage AI/ML workloads in a hybrid setup with geographic flexibility, working closely with DevOps, MLOps, and data teams to strengthen CI/CD and automation.

Qualifications

• 3–5 years of Level 2 production support experience.
• Strong UNIX/Linux, SQL, and scripting skills.
• Experience with cloud-native apps, distributed systems, containers, and Kubernetes.
• Familiar with CI/CD pipelines and GitLab.
• Experience with monitoring/observability tools (Splunk, Grafana, Prometheus).
• Knowledge of ITIL incident, problem, change management.
• Analytical and problem-solving with client-service mindset.
• Ability to troubleshoot data pipelines, workflows, and deployments.

Responsibilities

• Monitor, troubleshoot, and resolve Level 2 production incidents across AI platforms, cloud infrastructure, data pipelines, and model-serving environments.
• Provide hands-on support for deployment, orchestration, and operational management of AI/ML workloads in cloud-native environments.
• Build and maintain monitoring, alerting, and observability for infrastructure, applications, data pipelines, and model operations.
• Perform root cause analysis for production issues and drive permanent fixes.
• Collaborate with DevOps, MLOps, data engineering, and platform teams to maintain and enhance CI/CD and deployment automation.
• Develop automation, self-service tooling, and self-healing controls to reduce manual effort.
• Monitor and troubleshoot batch processes, workflow orchestration, data ingestion, model training, and deployments.
• Apply ITIL-based incident, problem, change, and release management to support stable operations.
• Analyse support-ticket and incident trends; propose operational improvements and AI-driven automation.

Skills

UNIX/Linux

SQL

Shell scripting

Python scripting

Cloud-native apps

Kubernetes

Containers

CI/CD pipelines

GitLab

Monitoring & observability

ITIL incident management

Analytical thinking

Tools

Splunk

Grafana

AppDynamics

Prometheus

Ansible

Terraform

Job description

As of now regular shift during US hours. Hybrid work ( 3 days from Office is Mandatory and 2 days remote)
Location: Lake Mary or 240 NY Office

Key Responsibilities

• Monitor, troubleshoot, and resolve Level 2 production incidents across AI platforms, cloud infrastructure, data pipelines, model-serving environments, and associated services.
• Provide hands-on support for deployment, orchestration, and operational management of AI/ML workloads across cloud-native environments.
• Build and maintain monitoring, alerting, and observability capabilities for infrastructure, applications, data pipelines, model operations, and distributed compute workloads.
• Perform root cause analysis for production issues, implement permanent fixes, and drive problem-management activities to improve service reliability.
• Collaborate with DevOps, MLOps, data engineering, platform engineering, and application teams to maintain and enhance CI/CD and deployment automation.
• Develop and support automation, self-service tooling, recovery mechanisms, and self-healing controls to reduce manual operational effort.
• Monitor and troubleshoot batch processes, workflow orchestration, data ingestion, model training, and model deployment failures.
• Apply ITIL-based incident, problem, change, and release management processes to support stable production operations.
• Analyse support-ticket and incident trends; recommend and implement operational improvements, including AI-driven automation where appropriate.

Qualifications & Skills

Mandatory:

• 3–5 years of experience in Level 2 application, platform, DevOps, or production support roles.
• Strong hands-on experience with UNIX/Linux, SQL, and shell or Python scripting.
• Experience troubleshooting cloud-native applications, distributed systems, containers, and Kubernetes-based environments.
• Working knowledge of CI/CD pipelines, deployment automation, and source-control platforms such as GitLab.
• Experience with monitoring, logging, and observability tools such as Splunk, Grafana, AppDynamics, Prometheus, or similar tools.
• Understanding of incident management, root cause analysis, problem management, and ITIL support processes.
• Strong analytical and problem-solving skills, with a client-service mindset.
• Ability to troubleshoot data-pipeline, workflow, API, and production deployment issues.

Good-to-Have:

• Exposure to MLOps practices, including model deployment, model monitoring, feature/data pipelines, and AI workload orchestration.
• Experience with cloud platforms such as AWS, Azure, or GCP.
• Experience with infrastructure automation and configuration-management tools such as Ansible, Terraform, or Ansible Tower.
• Familiarity with workflow and job-scheduling tools, such as Contro-M or equivalent enterprise schedulers.
• Knowledge of Docker, Kubernetes, and distributed compute/data-processing technologies.
• Exposure to Kafka, MQ, or other messaging and event-streaming platforms.
• Experience implementing self-healing, auto-remediation, resilience, backup, or disaster-recovery mechanisms.
• Familiarity with AI-driven operational tooling, ticket-trend analysis, or automation agents.