Lead DevOps Engineer

We are building an Agentic AI platform for Neurology that processes sensitive clinical data across a multi-tenant, multi-cloud environment serving a large number of clients. Each tenant operates in a hybrid setup — a mix of cloud-hosted services and on-premise appliances deployed at client sites. We're looking for a Lead DevOps Engineer to own the infrastructure, establish production-grade orchestration, harden security across tenant boundaries, and build scalable, repeatable delivery pipelines. This is a hands-on leadership role. You'll shape the DevOps roadmap, enforce engineering discipline across deployments, and mentor a small team — all while keeping a complex hybrid, multi-tenant environment running reliably.

What You'll Do

Multi-Cloud & Multi-Tenant Infrastructure:

• Design and manage infrastructure across AWS and GCP, ensuring consistent networking, security, and deployment patterns across both clouds.
• Architect tenant-isolated environments with secure VPC networking — no public-facing IPs, private subnets, VPC peering, endpoints, and VPN connectivity.
• Build and operate production Kubernetes clusters to host containerized microservices at scale.
• Define the strategy for which workloads run where — cloud vs. on-premise — based on data sensitivity, latency, and compliance requirements.

• Own and evolve a centralized, modular CI,CD pipeline built on GitHub Actions as the single path to production.
• Eliminate direct developer access to production environments; implement controlled deployment workflows using session-based access tools (e.g., AWS SSM Session Manager).
• Establish branch protection, image signing, environment promotion gates, and tenant-aware deployment strategies.

• Oversee configuration management for client-site appliances using Chef for example in a client-server architecture.
• Drive the strategy to progressively centralize microservices into cloud-hosted infrastructure, minimizing the on-premise footprint.
• Define remote access procedures, failure runbooks, and contingency workflows for on-premise hardware.

• Enforce infrastructure security best practices for a healthcare environment handling PHI and de-identified clinical data across tenant boundaries.
• Manage VPN-based access to private cloud networks and implement least-privilege IAM, secrets management, and policy-as-code across all environments.
• Ensure tenant data isolation at the network, storage, and compute layers.

• Build and maintain unified observability using Prometheus and Grafana across cloud and on-premise environments.
• Own the backup and disaster recovery strategy — container registries, automated snapshots, and cross-cloud resilience.
• Define and track SLOs for critical data pipelines and tenant-facing services.

• Mentor junior DevOps,infrastructure engineers and collaborate closely with data engineering, AI, and IT teams.
• Recommend and help hire for supporting roles (e.g., IT support for on-premise hardware operations).
• Establish DevOps standards, documentation, and runbooks for the team.

Must Have

• 6+ years of DevOps,Infrastructure,SRE experience, with at least 2 years in a lead or senior capacity.
• Production experience across AWS and GCP — VPCs, IAM, compute, storage, and managed services on both platforms.
• Hands-on experience running Kubernetes in production — cluster lifecycle, Helm charts, service mesh, autoscaling, and troubleshooting.
• Deep expertise in CI,CD design using GitHub Actions (or comparable platforms) with a focus on security and governance.
• Strong understanding of multi-tenant architecture patterns — network isolation, tenant-aware deployments, and data segregation.
• Solid Docker and container lifecycle management experience.
• Infrastructure-as-Code proficiency with Terraform (multi-provider) or equivalent.
• Networking fundamentals — VPNs, VPCs, DNS, firewalls, load balancers, and zero-trust architectures.
• Comfort with Python and shell scripting for automation.
• A production-first, outcome-oriented mindset — you measure success by what's running reliably in production, not by what's in a slide deck. Customer value over story-point velocity.
• Excellent communication skills — you can translate complex technical concepts for both engineering peers and business stakeholders.

• 1+ years of DevOps team management experience — you've directly managed devops engineers, run standups, handled performance conversations, and built team culture.
• Experience with the AI-native stack — vector databases (Pinecone, Weaviate,pgvector), RAG pipelines, feature stores, LLM orchestration frameworks(LangChain, LlamaIndex), and ML pipeline tooling (MLflow, Kubeflow,SageMaker).
• Experience in healthcare, life sciences, or any environment with strict data privacy requirements (HIPAA, PHI handling).
• Experience with configuration management tools such as Chef, Ansible, or Puppet.
• Familiarity with Elasticsearch operations and management.
• Experience managing hybrid environments with on-premise hardware alongside cloud infrastructure.
• Exposure to Prometheus, Grafana, and alerting pipeline design.
• Background working with data engineering teams running ETL,ELT pipelines.