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DevOps Engineer
Vernacular.ai's logo

DevOps Engineer

Bablu Kumar's profile picture
Posted by Bablu Kumar
2 - 5 yrs
₹8L - ₹12L / yr
Bengaluru (Bangalore)
Skills
DevOps
skill iconDocker
skill iconKubernetes
skill iconAmazon Web Services (AWS)
Bash
skill iconPython
skill iconJenkins
SRE
  • 2+ years of demonstrable experience leading site reliability and performance in large-scale, high-traffic environments
  • 2+ years of hands-on experience as a DevOps engineer
  • Strong leadership, communication and interpersonal skills geared to getting things done
  • Developing themselves and the talent within their charge – fostering and creating opportunity for the team
  • Strong understanding of SRE concepts and the DevOps culture. Set the direction and strategy for your team, and help shape the overall SRE program for the company
  • Be able to lead complicated technical issues and communicating status updates/RCA with management and customers.
  • Own site stability, performance, capacity planning, DevOps recruitment.
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Shubham Vishwakarma

Full Stack Developer - Averlon
I had an amazing experience. It was a delight getting interviewed via Cutshort. The entire end to end process was amazing. I would like to mention Reshika, she was just amazing wrt guiding me through the process. Thank you team.
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About Vernacular.ai

Founded :
2016
Type :
Product
Size :
20-100
Stage :
Raised funding

About

With our multi-lingual Conversational AI Platform, automate your industry, bring efficiency to your operational activities & provide better customer experience. Click to know more!
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Connect with the team

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Abhishek Ekka
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Mithun Arunan
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Bablu Kumar

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ROLE & RESPONSIBILITIES:

We are hiring a Senior DevSecOps / Security Engineer with 8+ years of experience securing AWS cloud, on-prem infrastructure, DevOps platforms, MLOps environments, CI/CD pipelines, container orchestration, and data/ML platforms. This role is responsible for creating and maintaining a unified security posture across all systems used by DevOps and MLOps teams — including AWS, Kubernetes, EMR, MWAA, Spark, Docker, GitOps, observability tools, and network infrastructure.


KEY RESPONSIBILITIES:

1.     Cloud Security (AWS)-

  • Secure all AWS resources consumed by DevOps/MLOps/Data Science: EC2, EKS, ECS, EMR, MWAA, S3, RDS, Redshift, Lambda, CloudFront, Glue, Athena, Kinesis, Transit Gateway, VPC Peering.
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  • Harden VPC architecture, subnets, routing, SG/NACLs, multi-account environments.
  • Ensure encryption of data at rest/in transit across all cloud services.

 

2.     DevOps Security (IaC, CI/CD, Kubernetes, Linux)-

Infrastructure as Code & Automation Security:

  • Secure Terraform, CloudFormation, Ansible with policy-as-code (OPA, Checkov, tfsec).
  • Enforce misconfiguration scanning and automated remediation.

CI/CD Security:

  • Secure Jenkins, GitHub, GitLab pipelines with SAST, DAST, SCA, secrets scanning, image scanning.
  • Implement secure build, artifact signing, and deployment workflows.

Containers & Kubernetes:

  • Harden Docker images, private registries, runtime policies.
  • Enforce EKS security: RBAC, IRSA, PSP/PSS, network policies, runtime monitoring.
  • Apply CIS Benchmarks for Kubernetes and Linux.

Monitoring & Reliability:

  • Secure observability stack: Grafana, CloudWatch, logging, alerting, anomaly detection.
  • Ensure audit logging across cloud/platform layers.


3.     MLOps Security (Airflow, EMR, Spark, Data Platforms, ML Pipelines)-

Pipeline & Workflow Security:

  • Secure Airflow/MWAA connections, secrets, DAGs, execution environments.
  • Harden EMR, Spark jobs, Glue jobs, IAM roles, S3 buckets, encryption, and access policies.

ML Platform Security:

  • Secure Jupyter/JupyterHub environments, containerized ML workspaces, and experiment tracking systems.
  • Control model access, artifact protection, model registry security, and ML metadata integrity.

Data Security:

  • Secure ETL/ML data flows across S3, Redshift, RDS, Glue, Kinesis.
  • Enforce data versioning security, lineage tracking, PII protection, and access governance.

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  • Implement drift detection (data drift/model drift), feature monitoring, audit logging.
  • Integrate ML monitoring with Grafana/Prometheus/CloudWatch.


4.     Network & Endpoint Security-

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  • Secure remote workforce connectivity and internal office networks.


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  • Ensure compliance with ISO 27001, SOC 2, GDPR, HIPAA (as applicable).
  • Maintain security policies, procedures, RRPs (Runbooks), and audits.


IDEAL CANDIDATE:

  • 8+ years in DevSecOps, Cloud Security, Platform Security, or equivalent.
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  • Experience securing ML platforms, data pipelines, and MLOps systems (Airflow/MWAA, Spark/EMR).
  • Strong Linux security (CIS hardening, auditing, intrusion detection).
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  • Understanding of microservices, API security, serverless security.
  • Strong understanding of vulnerability management, penetration testing practices, and remediation plans.


EDUCATION:

  • Master’s degree in Cybersecurity, Computer Science, Information Technology, or related field.
  • Relevant certifications (AWS Security Specialty, CISSP, CEH, CKA/CKS) are a plus.


PERKS, BENEFITS AND WORK CULTURE:

  • Competitive Salary Package
  • Generous Leave Policy
  • Flexible Working Hours
  • Performance-Based Bonuses
  • Health Care Benefits
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Position
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Location
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Utilize various open source technologies and tools to orchestrate solutions
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Configuration and management of data sources like MySQL, Mongo, Elasticsearch, Redis, Cassandra, Hadoop, etc.
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Shubham Vishwakarma

Full Stack Developer - Averlon
I had an amazing experience. It was a delight getting interviewed via Cutshort. The entire end to end process was amazing. I would like to mention Reshika, she was just amazing wrt guiding me through the process. Thank you team.
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