Job Posting Title AI/ DevOps Engineer

AdobeSan Jose, CA
$173,500 - $331,050

About The Position

Senior SRE — RTCDP Datastores & AI/ML Ops Adobe’s Real-Time Customer Data Platform (RTCDP) powers personalized experiences for some of the world’s largest brands. As a Senior SRE on this team, you’ll be central to keeping RTCDP reliable, scalable, and operationally excellent at global scale. This is a hands-on, high-ownership role at the intersection of production operations (Day 2 ownership) and core datastore engineering, with a growing surface area in operationalizing AI/ML services and workflows.

Requirements

  • 6–10 years in SRE, infrastructure, or platform engineering
  • Proven track record operating large-scale distributed systems in production
  • Strong foundation in datastores, reliability engineering, and automation
  • Hands-on experience with Kubernetes and containerized environments, a major cloud (AWS, Azure, or GCP), and modern observability tooling (Prometheus, Grafana, OpenTelemetry, or equivalents)
  • Real experience in incident response and driving operational improvements out of it
  • Working knowledge of — or genuine interest in — AI/ML systems or MLOps (expertise not required)
  • Comfortable with scale, ambiguity, and high ownership
  • Strong problem-solving instincts and a bias for action

Responsibilities

  • Own production reliability: Own day-to-day reliability for RTCDP services — availability, performance, and durability against SLOs. Participate in on-call rotations and incident response, driving mitigation and recovery through SEV3–SEV1 events. Lead post-incident reviews and follow-up work. Strengthen operational readiness, playbooks, and on-call health. Partner with product and platform teams on production-ready launches and regional expansions.
  • Operate and evolve core datastores: Work across RTCDP’s distributed datastore ecosystem: Aerospike, FoundationDB, Postgres, and CosmosDB/DynamoDB. Drive reliability, scaling, and operational excellence across these platforms. Own upgrades, capacity management, backup/restore, and DR testing. Build automation for provisioning, scaling, and lifecycle management. Identify and ship cost optimizations (rightsizing, storage/compute efficiency).
  • Drive automation and observability: Build automation-first solutions that reduce toil and improve system safety. Improve monitoring, alerting, and observability — anchored to real customer impact. Establish standardized operational patterns across services and regions. Support the rollout of SLO-driven reliability practices.
  • Contribute to AI/ML Ops (emerging area): Support infrastructure and operational needs for AI/ML-powered services in RTCDP. Shape operational practices for model serving and data pipelines — reliability, scaling, monitoring. Help land core MLOps patterns where relevant: model deployment workflows, inference observability (latency, errors), data quality and pipeline reliability signals. Partner with ML and data teams to get AI-driven features production-ready. Leverage AI-assisted tools (e.g., Copilot, Claude Code, Codex, internal tooling) to accelerate debugging, incident response, and operational workflows.
  • Technical leadership and collaboration: Operate as a strong IC and technical lead on cross-cutting projects. Mentor junior engineers and raise team practices. Partner closely with engineering, infrastructure, and security. Live the core SRE/DevOps principles: ownership, automation, error budgets, continuous improvement.

Benefits

  • Comprehensive benefits programs
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