Director, Technical Operations

Coca-Cola•Atlanta, GA

2d•Onsite

About The Position

The Director, Tech Operations leads global technology operations for Coca-Cola’s MarTech and AdTech platforms, with end-to-end accountability for Level 2 incident resolution, platform reliability, and operational excellence across all regions. The role brings an AI-augmented, agent-driven approach to how operations are run, monitored, and continuously improved. The Director is a technologist who understands the platforms deeply, works hand in hand with the development teams, and leads a team that builds and maintains AI agents for monitoring, detection, diagnosis, and automated remediation of systems and platforms worldwide. The successful leader pairs strong operational discipline with GenAI fluency, raising service quality and resilience while reducing manual toil and mean time to resolution.

Requirements

10+ years of experience in technology operations or engineering, including significant experience leading L2/production operations or SRE for large-scale, high-availability platforms, with proven people-leadership.
Hands-on technical depth: strong understanding of cloud platforms (GCP, AWS, or Azure), distributed systems, APIs, and modern observability tooling, with the credibility to work directly with development teams.
AIOps & agentic operations (Preferred): demonstrated experience applying AI/ML and GenAI to operations, including anomaly detection, event correlation, automated remediation, and building or operating AI agents and agentic workflows for monitoring.
GenAI literacy: familiarity with LLM integration, agent frameworks, RAG, evaluation and guardrails, and the security and cost disciplines of running AI in production.
Operational rigor: deep grasp of incident management, on-call, runbook automation, CI/CD, and reliability engineering, with a track record of reducing MTTR and manual toil.
Transformation leadership: proven ability to modernize a traditional support or operations function into an automated, outcome-driven model, including upskilling and reshaping teams.
Global team leadership: experience leading globally distributed operations teams, including a mix of in-house and strategic vendor talent, across regions.
Communication: strong written and verbal communication, able to align stakeholders and translate operational performance into business outcomes for executives.
Bachelor’s degree in engineering, computer science, or related field; advanced degree preferred. An equivalent combination of relevant education, training, and demonstrated experience is also considered.

Nice To Haves

AIOps & agentic operations
Advanced degree preferred

Responsibilities

Own global Level 2 (L2) operations and incident resolution for MarTech / AdTech platforms, leading a follow-the-sun team to deliver high reliability, fast resolution, and a consistently strong service experience.
Lead the team that builds and maintains AI agents for monitoring and operations: agentic detection, event correlation, alert-noise reduction, automated triage, root-cause analysis, and self-healing remediation across systems and platforms globally.
Drive the shift from traditional ticket processing to AI-augmented operations, redesigning workflows, runbooks, and team roles around GenAI capabilities and intelligent automation rather than manual handling.
Stay deeply technical: understand the platforms and architecture well enough to partner directly with development teams on observability, instrumentation, reliability fixes, and operability of new releases.
Advance observability and reliability maturity (SRE / SLOs): improve telemetry across logs, metrics, and traces, strengthen incident-response readiness, and enforce root-cause-analysis discipline that prevents repeat incidents.
Establish guardrails and governance for operational AI: ensure agents act safely and within policy, with human-in-the-loop controls, safe rollback, and resilience against unsafe actions, prompt injection, and data exposure.
Build and lead a tech-savvy, GenAI-literate operations team, upskilling talent from traditional support toward AIOps, automation, and agent operations, and recruiting new capabilities where gaps exist.
Identify systemic bottlenecks in reliability, performance, cost, and operational toil, and lead improvements that compound over time across the global platform estate.
Partner with Engineering, Product, Security, and regional stakeholders to align on operational readiness, release operability, and clear ownership of risks and dependencies.
Define and report operational metrics (MTTR, MTTD, uptime/SLOs, automation rate, ticket deflection, cost-to-serve) to leadership, demonstrating the business value of the AI-augmented operating model.