Automation Specialist

Role & responsibilities

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.