Staff Engineer, Machine Learning Operations

📋 Description

• • Own the technical North Star for Nextgen’s AI platform, translating ambitious product goals into a resilient, multi-region, multi-tenant architecture that supports both real-time inference and large-scale training jobs with strict tenant isolation and cost-efficiency.
• • Architect and continuously evolve the end-to-end ML-AIOps stack—from raw data ingestion through feature engineering, model training, agent deployment, and product integration—ensuring every layer is observable, governable, and secure.
• • Define and implement a battle-tested CI/CD strategy for models, agents, and data pipelines that includes policy gates, automated canary rollouts, blue-green deployments, and instant rollback mechanisms to guarantee zero-downtime releases.
• • Institutionalize enterprise-grade monitoring and alerting for model quality, safety, drift, latency, and business KPIs; sponsor always-on evaluation suites and feedback loops that surface anomalies before customers feel them.
• • Lead cross-functional reliability programs: capacity planning, disaster-recovery playbooks, quarterly chaos-engineering drills, and 24×7 incident management that keep p99 latency under tight SLAs even during traffic spikes.
• • Establish governance guardrails for datasets, prompts, models, and agents—covering lineage, versioning, approvals, and audit trails—so compliance, security, and product teams can trace every decision from ideation to production.
• • Partner with Security & Compliance to bake zero-trust principles, key-management vaults, secrets rotation, and continuous audit logging into the DNA of the platform, passing SOC 2, HIPAA, and ISO 27001 reviews with ease.
• • Evaluate build-vs-buy decisions for critical platform components (feature stores, vector DBs, GPU schedulers, LLM serving frameworks); negotiate with vendors, manage technical debt, and maintain a 3-year technical roadmap aligned to business OKRs.
• • Mentor a growing team of MLOps, SRE, and data engineers; foster a culture of documentation, blameless post-mortems, and reusable runbooks that turn tribal knowledge into institutional knowledge.
• • Champion cost governance by designing autoscaling policies, spot-instance orchestration, and GPU utilization dashboards that cut cloud spend without compromising performance.
• • Collaborate with Product, Data Science, and Customer Success to translate clinical workflows into scalable AI services, ensuring that every model shipped measurably improves patient outcomes.
• • Drive the adoption of modern tooling—Terraform for IaC, Kubernetes for orchestration, MLflow for experiment tracking, DataDog/Dynatrace for observability—while customizing them to the unique demands of healthcare AI.
• • Contribute to open-source communities and internal guilds, sharing best practices for LLM observability, agent orchestration, and privacy-preserving ML that elevate Nextgen’s reputation as an industry thought leader.
• • Perform additional duties as needed to support the overarching mission of delivering resilient, cost-effective AI that empowers ambulatory healthcare providers to build healthier communities.