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Senior Site Reliability Engineer – L3 (AI/ML)

Recruitingbond · Hyderabad, Telangana, India

Jun 29
Senior (5-10 yrs) Full-time India
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About the role

Own the infrastructure architecture, scalability, and reliability for AI-scale healthcare workflows. Lead the design of secure AWS/GCP architectures and manage GPU workload orchestration and SRE practices.

What they look for

AWS GCP Kubernetes Terraform GitOps Python Go Bash AI/ML Infrastructure GPU Orchestration SRE DevSecOps Incident Management Infrastructure as Code SLO/SLI Definition SOC 2/HIPAA Compliance

Requirements

Requires 5-8 years of experience in SRE or DevOps with deep expertise in AWS, GCP, and advanced Kubernetes. Must have a proven track record in scaling AI/ML inference and GPU infrastructure in production.

Full description

Senior Site Reliability Engineer – L3

Senior SRE Engineer

📍 Location: Hyderabad, India

📍 Work Type: Full-Time | On-site / Hybrid

📍 Experience: 5–8 Years

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Role Overview

Own infrastructure architecture, scalability, and reliability. Set technical direction, define SRE practice, and mentor engineers. Build and operate AI-scale infrastructure powering real-time healthcare workflows.

Key Responsibilities

Architecture & Platform

  • Design scalable, secure, cost-efficient AWS/GCP architectures for AI and healthcare workloads
  • Lead IaC standards and reusable modules org-wide; own GitOps practices
  • Architect optimized Kubernetes (EKS/GKE) for HA, scale, and GPU workload orchestration

Reliability Engineering

  • Define and drive reliability targets (SLOs/SLIs); establish SRE practice
  • Lead incident management, RCA, and blameless post-mortems for critical systems
  • Partner on infrastructure hardening and compliance (SOC 2, HIPAA)

AI-First Engineering

  • Lead AI/ML inference and GPU infrastructure scaling in production
  • Evaluate and introduce AI tooling, platforms, and automation best practices
  • Contribute to LLM deployment pipelines and AI systems reliability

Leadership & SDLC

  • Mentor L1/L2 engineers; influence cross-team infrastructure decisions
  • Drive DevSecOps maturity across the SDLC (policy-as-code, SBOM, supply-chain security)
  • Evaluate and introduce new tooling and platforms

Requirements

  • 5–8 years infrastructure/platform/DevOps/SRE
  • Deep expertise in AWS & GCP large-scale production systems
  • Advanced Kubernetes (cluster design, multi-tenant ops, resource quotas)
  • AI/ML inference or GPU infrastructure scaling (production track record)
  • Strong Terraform / equiv. and GitOps practices
  • Python, Go, or Bash scripting and automation
  • Track record in scale, reliability, and cost efficiency
  • Lead incident response and on-call practices

Nice-to-Have

  • LLM Gateway architecture and optimization
  • Zero-trust networking and advanced security/compliance (SOC 2, HIPAA)
  • DevSecOps maturity: SBOM, supply-chain security, policy-as-code
  • Open-source contributions or platform-team leadership

Why This Opportunity?

  • Build infrastructure and products powering real-world healthcare AI
  • Work with AI-native engineering teams using cutting-edge tools (Claude Code, Cursor, Copilot)
  • Mission-driven impact — improve patient outcomes and save thousands of staff hours
  • High ownership, rapid learning, and significant career upside
  • Global collaboration across India and the US
  • Seed-stage growth — scale from Seed to Series A alongside the team