Automation Specialist
Summary
Builds and maintains automation for enterprise integration platforms (webMethods, MuleSoft, or IBM Integration), DataStage data pipelines, and Control-M job scheduling, using Python, Linux shell scripting, and AWS. The role also explores agentic AI/LLM-based automation for incident triage and self-healing workflows.
Role & responsibilities
Job Title :- Automation Specialist
Locations :- Bengaluru
Experience :- 4-7 years
Mandatory Skills :- Python,AWS
Roles & Responsibilities
- Build and maintain automation for integration platform operations across one or more of: webMethods, MuleSoft, or IBM Integration (App Connect/IIB).
- Support and automate data pipeline workflows on DataStage.
- Design and manage job scheduling and workflow automation using Control-M, including dependencies, SLA monitoring, and failure recovery.
- Develop automation scripts and tooling in Python to streamline repetitive operational tasks across the integration stack.
- Deploy and manage automation workloads leveraging AWS cloud services (compute, storage, serverless/Lambda, monitoring).
- Explore and apply agentic AI approaches (e.g., AI agents/LLM-based automation) to drive intelligent incident triage, self-healing workflows, and reduction of manual operational effort.
- Partner with platform engineering, SRE, and application teams to identify automation opportunities and convert manual runbooks into automated, self-service solutions.
- Monitor integration workflows end-to-end and build automated alerting/remediation to minimize downtime.
- Document automation solutions, runbooks, and standard operating procedures.
- Participate in support rotations as needed for critical automation or platform issues.
- Linux Shell scripting skills are required
- DevOps exposure is required
- Preferred Qualifications
- Experience with CI/CD tools (Jenkins, GitLab CI) and version control (Git).
- Exposure to Infrastructure-as-Code (Terraform, CloudFormation).
- Familiarity with monitoring/observability tools (Splunk, Dynatrace, Grafana).
- Prior experience in a large-scale enterprise integration environment.
- Relevant certifications (AWS, webMethods, MuleSoft, or IBM Integration) are a plus.
- Soft Skills
- Curiosity and willingness to pick up new tools across a varied integration stack.
- Automation-first mindset with practical problem-solving skills.
- Ability to collaborate across SRE, platform engineering, and application teams.
- Clear documentation and communication skills.
- Comfortable operating in a fast-paced, incident-driven environment.
Preferred candidate profile
- Decent, hands-on exposure to at least one integration platform: webMethods, MuleSoft, or IBM Integration (App Connect/IIB/MQ).
- Working knowledge of DataStage (or similar ETL/data integration tools).
- Experience with Control-M or similar workload automation/job scheduling tools.
- Proficiency in Python for scripting and automation development.
- Exposure to AWS cloud infrastructure (EC2, Lambda, S3, CloudWatch, IAM basics).
- Interest in or hands-on exposure to agentic AI / LLM-based automation (e.g., building or using AI agents for operational tasks).
- Understanding of APIs (REST/SOAP) and messaging concepts.
- Comfortable working across a broad toolset rather than deep specialization in a single platform.