Responsibilities:

Design and implement solutions to enhance the reliability and scalability of AI/ML platforms and applications to accommodate fast growing demands. Partner with product engineering teams to ensure the AI/ML systems are reliable and high performing.  Develop observability, security, automation and fin-ops tools and orchestration. Provide strategic technology leadership by defining and evaluating standards and architecture for reliability, observability and automation frameworks. Build strong cross-functional relationships that foster engagements across the organization and deliver solutions to user problems. Debug and solve issues in a production environment, identify root cause and remediate.  Participates in on-call rotations, incident management and escalation workflows. Take full ownership of problems, develop solutions, and acquire new knowledge to complete the task. Mentor and guide junior engineers.

Required Qualifications:

Bachelor’s degree in computer science, Information Technology, or equivalent technical qualification with 5+ years professional experience. Expertise in SRE principles, reliability, scalability and performance of application and infrastructure. Have hands-on experience with cloud platforms (AWS, GCP, Azure) and IaC tools (Terraform, Ansible).  Extensive experience implementing advanced observability using tools like Open Telemetry, Dynatrace, Grafana, and/or cloud-native services. Experience in architecting distributed systems and cloud-native architecture in AWS. Systematic problem-solving and troubleshooting skills in a complex system. Excellent communication skills and ability to represent and present business and technical concepts to stakeholders.  Self-managed, self-motivated with strong sense of ownership, urgency, and drive

Good to have:

Prior experience working in AI, ML, or Data engineering. Prior experience developing AI Ops/AI Agents. Multi cloud experience (AWS, GCP, Azure) is a plus