DevOps Engineer (DW US to India Offshoring)

POSITION:

Reporting to the Manager Software Engineering were seeking a mid-level DevOps Engineer who can design automate and scale cloud-native infrastructure and CI/CD pipelines. Youll collaborate closely with product data and ML engineering teams to enable rapid reliable deliveryincluding MLOps workflows for training deploying and monitoring machine learning models in production.

RESPONSIBILITES:

Platform & Automation

• Design implement and maintain CI/CD pipelines using GitHub Actions Jenkins and ArgoCD for application and ML model delivery.
• Build Infrastructure as Code (IaC) with Terraform and Ansible across environments (dev/stage/prod).
• Containerize services with Docker and manage orchestration on Kubernetes (including Helm charts Operators and secrets management).
• Implement artifact versioning and release management for application and ML model artifacts.

Cloud & Networking

• Deploy and operate workloads on AWS (EC2 ECS/EKS Lambda S3 CloudFront ELB) and integrate security controls (IAM Cognito Secrets Manager/Vault).
• Support multi-cloud patterns (basic exposure to GCP: BigQuery Pub/Sub Dataflow; Azure: Data Factory Synapse Analytics) for data/ML pipelines.
• Optimize networking load balancing caching (e.g. ElastiCache/Redis) and CDN configurations for performance and cost-efficiency.

Observability & Reliability

• Implement end-to-end monitoring logging and tracing with Prometheus Grafana Loki Jaeger OpenTelemetry.
• Establish SLOs/SLIs alerting and incident workflows using PagerDuty/Opsgenie; drive post-incident reviews and reliability improvements.
• Build observability for ML systems (data drift model performance metrics feature store health pipeline latency).

Security & Compliance

• Enforce security-by-design: least-privilege IAM vulnerability scanning image signing Lets Encrypt and certificate automation.
• Implement secrets and keys management via Vault and AWS Secrets Manager.
• Support data governance & compliance (e.g. GDPR HIPAA) alongside engineering and risk teams; contribute to audit-ready documentation.

Data/ML & MLOps Enablement

• Productionize ML workflows using MLflow (tracking model registry) and Kubeflow (pipelines serving).
• Support Generative AI integrations and RAG pipelines on Amazon Bedrock and model endpoints (e.g. Anthropic Claude).
• Operationalize ETL/ELT jobs and data pipelines with Airflow/dbt PySpark and streaming systems (Kafka RabbitMQ).
• Partner with data scientists/ML engineers to standardize feature stores model packaging A/B testing canary/blue-green deployments and shadow mode releases.
• Set up model monitoring: accuracy/latency data quality concept drift and automated rollback or retraining triggers.

Collaboration & Quality

• Work closely with product managers and cross-functional teams to deliver software solutions.
• Participate in agile development processes including design implementation and deployment.
• Write technical documentation and contribute to end-user guides.

REQUIREMENTS:

• 35 years in DevOps/SRE or platform engineering roles.
• Strong hands-on with Docker and Kubernetes (Helm Operators multi-namespace/multi-tenant setups).
• Proven experience building CI/CD with GitHub Actions Jenkins ArgoCD.
• Proficiency with Terraform (modules workspaces) and Ansible (playbooks roles).
• Solid AWS experience: EC2 ECS/EKS Lambda S3 CloudFront ELB and CloudWatch/X-Ray.
• Monitoring/observability using Prometheus Grafana Loki Jaeger OpenTelemetry.
• Scripting proficiency in Python and/or Bash.
• Understanding of security best practices secrets management (Vault/Secrets Manager) and compliance requirements (GDPR HIPAA).

• Experience with MLflow/Kubeflow and ML deployment patterns (batch/real-time serving GPU scheduling).
• Exposure to Amazon Bedrock Anthropic Claude and RAG architectures (vector stores embedding pipelines).
• Familiarity with dbt Airflow PySpark Kafka/RabbitMQ for data/ML pipelines.
• Knowledge of OpenSearch ElastiCache/Redis and PostgreSQL/MySQL/Snowflake.
• Performance tuning cost optimization (rightsizing spot instances autoscaling) and FinOps awareness.

Qualifications :

EDUCATIONAL QUALIFICATIONS

• Bachelors degree in Engineer Technology Computer Science Science
• 5-7 years relevant industry experience (Healthcare Pharmaceutical Consulting Management Consulting Hospital systems Payers Enterprise level data-analytical solutions)

Additional Information :

All your information will be kept confidential according to EEO guidelines.

Our team is aware of recent fraudulent job offers in the market misrepresenting EVERSANA. Recruitment fraud is a sophisticated scam commonly perpetrated through online services using fake websites unsolicited e-mails or even text messages claiming to be a legitimate company. Some of these scams request personal information and even payment for training or job application fees. Please know EVERSANA would never require personal information nor payment of any kind during the employment process. We respect the personal rights of all candidates looking to explore careers at EVERSANA.

From EVERSANAs inception Diversity Equity & Inclusion have always been key to our success. We are an Equal Opportunity Employer and our employees are people with different strengths experiences and backgrounds who share a passion for improving the lives of patients and leading innovation within the healthcare industry. Diversity not only includes race and gender identity but also age disability status veteran status sexual orientation religion and many other parts of ones identity. All of our employees points of view are key to our success and inclusion is everyones responsibility.

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Remote Work :

No

Employment Type :

Full-time