Senior Software Engineer

CVS Health•Woonsocket, RI

12d•Onsite

About The Position

We’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time. Position Summary: We are seeking a highly skilled backend-focused Senior Software Engineer to join our modernization team focused on transforming the legacy CVS pharmacy systems into a cutting-edge, cloud-native platform. As part of the team, you will play a crucial role in designing and developing microservices that drive the modernization of critical patient and drug domains. You will work on integrating cloud-native solutions, enhancing performance, and ensuring seamless operation within a highly scalable and secure environment. The ideal candidate will have extensive experience in backend development, system design, and a strong understanding of cloud-native software engineering principles.

Requirements

5+ years of experience building data pipelines or backend data workflows using Python, Java, or similar languages
2+ years of experience designing REST/GraphQL data services or integrating data APIs
2+ years of experience with cloud platforms (GCP, AWS or Azure)
2+ years of hands-on experience with Infrastructure as Code tools (Terraform preferred; Pulumi or CDK)
Bachelor’s degree or equivalent experience (HS diploma + 4 years relevant experience)

Nice To Haves

Hands-on experience working with ML/AI model integration in production (e.g., Vertex AI Endpoints, TensorFlow Serving, ML REST APIs)
Experience handling structured and unstructured datasets, including healthcare data (Rx claims, clinical documents, NLP text)
Direct, hands-on experience with Google Cloud Platform, especially BigQuery, Dataflow, GKE, Composer and Vertex AI
Knowledge of GenAI pipelines, LLM prompt workflows, and agent orchestration frameworks (e.g., LangChain, transformers)
Experience deploying Python-based ML/NLP services into microservice ecosystems using REST, gRPC, or sidecar architectures
Familiarity with GCP Shared VPC, VPC Service Controls, or private Google Access configurations for secure data platform networking
Exposure to FinOps practices — cloud cost attribution, showback/chargeback models, and resource tagging strategies

Responsibilities

Design, build, and maintain scalable data pipelines to support analytics, ML, and operational reporting
Develop robust data ingestion, transformation, and integration workflows using Python, SQL, and modern data engineering frameworks
Build and maintain batch and streaming data pipelines leveraging technologies such as Kafka (or similar pub/sub tools)
Work with Google Cloud Platform (GCP) services, including Cloud Storage, Dataflow, Pub/Sub, BigQuery, Cloud Spanner and Cloud Functions
Develop and manage data APIs and interfaces (REST and GraphQL) to enable high-performance data access across microservices
Implement CI/CD automation for data pipelines using GitHub Actions, Argo CD, or equivalent tools
Collaborate with Data Scientists and MLOps teams to integrate ML/NLP models into data pipelines and production workflows
Build and operationalize NLP data pipelines for structured and unstructured data sources (e.g., Rx claims, clinical documents)
Implement frameworks for observability and data quality, ensuring ML predictions, confidence scores, and fallback events are logged into data lakes or monitoring systems
Design and provision cloud infrastructure using Infrastructure as Code (IaC) tools such as Terraform or Pulumi for GCP resources including GKE clusters, Cloud SQL, VPC networks, IAM, and storage
Deploy, configure, and manage containerized data workloads using Kubernetes (GKE) — including deployments, autoscaling (HPA/VPA), namespaces, resource quotas, and health checks
Architect and maintain network topology for data platform environments — VPCs, subnets, firewall rules, private service access, Cloud NAT, and VPC Service Controls
Implement and enforce IAM policies, service account governance, and secrets management (GCP Secret Manager or HashiCorp Vault) to ensure least-privilege access across all data services
Build and maintain infrastructure monitoring and alerting using Cloud Monitoring, Prometheus, Grafana, or equivalent — covering pipeline latency, throughput, error rates, and resource utilization
Establish and maintain CI/CD pipelines for infrastructure changes using Terraform Cloud, GitHub Actions, or Argo CD, ensuring infrastructure drift detection and rollback capability
Manage environment parity (dev/staging/prod) for data platform infrastructure, including environment-specific configuration management and promotion workflows
Drive cloud cost governance — right-sizing compute resources, implementing committed-use discounts, setting up budget alerts, and producing cost attribution reports per workload
Design and implement disaster recovery, backup, and high-availability strategies for data stores, pipeline infrastructure, and ML serving endpoints
Collaborate with Security and Platform teams to ensure data infrastructure compliance with enterprise security policies, SOC 2, HIPAA, and CVS Health regulatory requirements