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AIOps Lead, Software Engineering - Zelis Healthcare
Software Engineer
Lead the design and delivery of AI‑driven operations platforms, leveraging Python, Machine Learning, and cloud services to automate monitoring, incident response, and performance optimization for healthcare finance solutions.
About the role
Key Responsibilities
- Architect and build scalable AIOps platforms that ingest, analyze, and act on telemetry from microservice ecosystems.
- Lead a cross‑functional engineering team in developing machine‑learning models for anomaly detection, root‑cause analysis, and automated remediation.
- Design and implement cloud‑native solutions on AWS, utilizing services such as Lambda, S3, and SageMaker, and orchestrate containers with Kubernetes.
- Collaborate with product, security, and operations stakeholders to define metrics, SLAs, and observability standards.
- Mentor engineers on best practices in data engineering, model deployment, and CI/CD pipelines for AI‑enabled services.
Requirements
- 5+ years of software engineering experience, with at least 2 years leading AIOps or observability initiatives.
- Strong proficiency in Python and building production‑grade machine‑learning pipelines.
- Hands‑on experience with AWS cloud services and container orchestration (Kubernetes/EKS).
- Demonstrated ability to design microservice architectures and implement data pipelines for large‑scale telemetry.
- Excellent communication skills and a track record of mentoring technical teams.
Skills
pythonmachine learningawskubernetes