About Signant Health
At Signant Health, we are on a mission to help bring life-changing treatments to patients faster. As a global leader in clinical trial technology and services, we operate at the intersection of science and innovation—partnering with biopharmaceutical companies to simplify trial execution and enhance the patient experience. With a collaborative culture, cutting-edge digital solutions, and a focus on real-world impact, Signant is where your work drives meaningful change in global healthcare.
Sr Cloud Ops Automation Engineer
KEY ACCOUNTABILITIES:
1. Design, build, and maintain AI-powered automations for deployment, runbooks, monitoring, and remediation across cloud environments (AWS/Azure), leveraging Python and infrastructure-as-code.
2. Operationalize and govern AI coding/agent tools (e.g., Claude Code, Gemini, AWS Q) in production, including policy controls, prompt libraries, evaluation, and usage analytics.
3. Develop and maintain MLOps/LLMOps pipelines for AI services and automations (CI/CD for prompts, models, agents, and workflows), with automated testing and rollback.
4. Create event-driven auto-remediation (e.g., for incidents, cost anomalies, drift) using serverless functions and workflow engines; implement guardrails and human-in-the-loop approvals.
5. Build observability for AI automations and applications (tracing, metrics, logging, RAG/LLM evals, hallucination/latency monitoring) and drive SLOs, error budgets, and availability targets.
6. Troubleshoot complex issues across cloud, containers, data, and AI toolchains; perform root cause analysis and drive corrective/preventive actions and knowledge-base updates.
7. Implement cost optimization and FinOps for AI/compute resources (right-size instances, token/throughput controls, caching, batching, spot/savings plans).
8. Migrate and modernize on-prem workloads to cloud using automated IaC patterns; containerize services and standardize environments for AI/automation workloads.
9. Enforce security and compliance for AI automations (secrets management, least privilege IAM, data loss prevention, PII redaction, audit trails, model and prompt change controls).
10. Participate in 24x7 on-call rotation for production AI automation platforms; improve reliability through chaos testing, game days, and post-incident action items.
KNOWLEDGE, SKILLS & ATTRIBUTES
Essential:
1. BS in Computer Science or related field; 3+ years (5+ preferred) in Agile/DevOps environments delivering production automations.
2. Strong Python for automation and services; proficiency with Terraform (or Pulumi) and at least one shell (Bash/PowerShell).
3. Hands-on with cloud platforms (AWS and/or Azure): compute, networking, IAM, serverless (Lambda/Functions), containers (EKS/AKS), and managed queues/workflows (e.g., Step Functions, Logic Apps).
4. Experience operationalizing AI tools and agents (Claude Code, Gemini, AWS Q, or similar), including prompt engineering, evaluations, and runtime governance.
5. Containerization and orchestration expertise (Docker, Kubernetes); configuration management with Ansible; packaging and artifact management (e.g., Artifactory).
6. CI/CD proficiency (Jenkins/GitHub Actions/Azure DevOps) for infrastructure, applications, and AI/ML assets; feature flags and canary/blue-green deployments.
7. Observability and monitoring (CloudWatch/Azure Monitor, Prometheus/Grafana, OpenTelemetry); incident management and RCA practices.
8. Data and integration fundamentals: REST/gRPC, event-driven patterns, message queues; familiarity with RDBMS (Postgres/MySQL/SQL Server) and secrets management (e.g., AWS Secrets Manager/Key Vault).
9. Security-by-design mindset: least-privilege IAM, network segmentation, compliance basics (SOC2/ISO), data privacy for AI usage, and secure prompt/model lifecycle.
10. Collaborative and autonomous: effective cross-functional communication, documentation discipline, and ownership of outcomes; comfortable with on-call.
Optional/Preferred:
- Experience with LLMOps/MLOps stacks (LangChain/LlamaIndex, Vector DBs like Pinecone/Bedrock KB/OpenSearch, MLFlow, SageMaker/Azure ML).
- Experience with policy-as-code (OPA/Conftest), drift detection, and IaC scanning.
- Knowledge of FinOps practices for AI workloads (token budgeting, rate limiting, caching strategies).
- Familiarity with web servers and legacy middleware (IIS, Tomcat, WebLogic/WebSphere, Apache) for modernization contexts.
Why Join Us
Join a global, mission-driven organization that’s redefining how clinical trials are executed through innovation, technology, and collaboration. In this role, you’ll contribute to improving patient outcomes while developing your expertise at the intersection of clinical operations and digital health technology.
At Signant Health, accepting difference isn’t enough—we celebrate it, we support it, and we nurture it for the benefit of our team members, our clients and our community. Signant Health is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or veteran status.
