DevOps Engineer (DW US to India Offshoring)

Company Description

At EVERSANA, we are proud to be certified as a Great Place to Work across the globe. We’re fueled by our vision to create a healthier world. How? Our global team of more than 7,000 employees is committed to creating and delivering next-generation commercialization services to the life sciences industry. We are grounded in our cultural beliefs and serve more than 650 clients ranging from innovative biotech start-ups to established pharmaceutical companies. Our products, services and solutions help bring innovative therapies to market and support the patients who depend on them. Our jobs, skills and talents are unique, but together we make an impact every day. Join us! 

Across our growing organization, we embrace diversity in backgrounds and experiences. Improving patient lives around the world is a priority, and we need people from all backgrounds and swaths of life to help build the future of the healthcare and the life sciences industry. We believe our people make all the difference in cultivating an inclusive culture that embraces our cultural beliefs.  We are deliberate and self-reflective about the kind of team and culture we are building. We look for team members that are not only strong in their own aptitudes but also who care deeply about EVERSANA, our people, clients and most importantly, the patients we serve.   We are EVERSANA.  

POSITION:

Reporting to the Manager, Software Engineering, we’re seeking a mid-level DevOps Engineer who can design, automate, and scale cloud-native infrastructure and CI/CD pipelines. You’ll collaborate closely with product, data, and ML engineering teams to enable rapid, reliable delivery—including 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, Let’s 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:

• 3–5 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.

 

EDUCATIONAL QUALIFICATIONS

• Bachelor's 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)

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 EVERSANA’s 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 one’s identity. All of our employees’ points of view are key to our success, and inclusion is everyone's responsibility.

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