Automation Specialist

Quess IT Solutions; Bengaluru; Hybrid; INR 1,500,000 - 2,200,000; Full time

Job summary

Quess IT Solutions is seeking an Automation Specialist in Bengaluru with 4–7 years of experience to design and maintain automation across integration platforms. The role focuses on Python scripting, AWS deployment, and DevOps practices within a fast-paced environment.

You will work with SRE, platform engineering and application teams to automate runbooks, implement monitoring, and document solutions for reliability and efficiency.

Qualifications

• 4-7 years of experience in automation and integration platforms.
• Proficiency in Python and AWS for automation tasks.
• Experience with Linux scripting, DevOps practices and CI/CD pipelines.
• Familiarity with workload automation tools and data integration workflows.
• Exposure to AI/LLM based automation is a plus.

Responsibilities

• Build and maintain automation for integration platform operations across webMethods, MuleSoft, or IBM Integration.
• Automate data pipelines and manage job scheduling with Control-M.
• Develop Python tooling to streamline operational tasks across the stack.
• Deploy and manage automation on AWS including serverless and monitoring.
• Contribute to incident triage, self-healing workflows, and automation documentation.

Skills

Python

AWS

Linux Shell scripting

DevOps

CI/CD

Git

AI automation

Tools

Jenkins

GitLab CI

Terraform

CloudFormation

webMethods

MuleSoft

IBM Integration (App Connect/IIB)

DataStage

Control-M

Splunk

Dynatrace

Grafana

Job description

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.