Director of Engineering, AI Data Fabric

F5 Networks • Seattle, WA

1d

About The Position

The Director of Engineering leads the organization responsible for F5’s AI Data Fabric, an OpenTelemetry-based platform that ingests, processes, transforms, stores, and serves telemetry from internal and external sources across F5’s businesses and platforms. The fabric underpins company-wide AI/ML, analytics, and data engineering workloads and serves as the system of record for product measurement and customer usage. The role will guide the platform’s next stage of growth, expanding into additional first-party F5 data centers and cloud providers while increasing availability, performance, and scale.

The organization owns the full modern data platform stack, from ingestion through retrieval, and the platform contracts relied on by AI/ML, analytics, data engineering, and the separate data catalog team. The director sets technical strategy, roadmap, engineering standards, and technology choices; leads engineering managers and teams; partners with Product, Finance, SRE, Security, Procurement, and engineering leadership; and remains technically engaged in architecture, trade-offs, and critical issues without being the primary hands-on contributor.

The role is accountable for platform reliability, data quality, security, privacy, auditability, and cost efficiency. It includes operating production services under formal SLOs and 24/7 accountability, leading regional expansion while meeting residency requirements, and improving telemetry-source onboarding and platform economics as data volume grows. F5 describes a supportive, inclusive environment with continuous learning, mentorship, and opportunities to shape the platform’s future.

Requirements

• At least 10 years of software engineering experience.
• At least 6 years managing engineers.
• At least 2 years managing managers.
• Experience leading an engineering organization through a major platform migration, expansion, or re-architecture without disrupting production.
• Track record of delivering and operating enterprise-scale data platforms under formal SLOs and 24/7 accountability.
• Experience growing engineering managers, including leveling, promotion, and performance management at the manager layer.
• Experience presenting technical strategy, risk, and investment trade-offs to executive leadership.
• Experience engineering data correctness into production pipelines, including validation, reconciliation, and automated detection of quality regressions.
• Experience designing platform APIs and data contracts used by AI/ML, analytics, and data engineering teams, including training and feature data delivery.
• Experience operating a platform whose data feeds billing or externally reported figures.
• Ability to lead teams through ambiguity and change, turning ill-defined problems into clear priorities and plans.
• Clear, candid communication and ability to influence cross-functional and executive stakeholders.
• Experience with production-scale distributed compute and streaming, such as Kafka, Flink, and Spark.
• Experience with analytical storage and query engines at scale, such as ClickHouse, StarRocks, Druid, and Trino, and open table formats such as Iceberg and Delta.
• Experience with Kubernetes at production scale as a platform substrate, including cluster and fleet management, scheduling, upgrades, and capacity.
• Experience with hybrid, multi-cloud infrastructure at production scale spanning two or more public clouds and on-premise or first-party data centers, including infrastructure as code, residency and sovereignty constraints, and workload portability.
• Experience with OpenTelemetry pipelines, including collectors, semantic conventions, and configuration.
• Experience setting organizational standards for observability, alerting, and incident response for production data pipelines.
• Experience with data security and privacy for a production data platform.
• Working expertise in Golang, Java, Python, or C++ sufficient to participate credibly in technical reviews.

Responsibilities

• Build, lead, and develop engineering managers by setting goals, coaching growth, evaluating performance, and maintaining high technical and delivery standards.
• Drive delivery across teams by allocating capacity to high-value work, tracking execution, surfacing risks early, and resolving cross-team dependencies.
• Partner with Product, Finance, SRE, Security, and engineering leadership to translate measurement needs into platform strategy and resourcing.
• Promote safe, pragmatic use of AI and LLMs to accelerate feedback loops, and have managers extend these practices across their teams.
• Measure outcomes and hold yourself and teams accountable for commitments.
• Own the platform’s technical strategy, multi-year roadmap, engineering standards, build-versus-buy decisions, and core technology selection.
• Manage vendor and licensing relationships, including partner selection, negotiating terms with Procurement and Finance, and holding vendors accountable.
• Lead phased expansion across more first-party F5 data centers and cloud providers while meeting residency requirements and maintaining a coherent platform.
• Own platform contracts relied on by AI/ML, analytics, data engineering, and the data catalog team; prioritize onboarding telemetry sources across teams.
• Ensure the reliability, accuracy, timeliness, and auditability of telemetry across onboarded sources.
• Own production health, including SLOs for ingestion, processing, and retrieval, on-call and incident command, and durable post-incident fixes.
• Own platform security and privacy, including data classification, PII handling, access control, threat modeling, and audit readiness.
• Manage platform efficiency and cost, including infrastructure spend, unit economics, and capacity decisions.
• Lead a platform expansion, migration, or re-architecture without disrupting production.
• Engineer data correctness into production pipelines through validation, reconciliation, and automated detection of quality regressions.
• Design platform APIs and data contracts for AI/ML, analytics, and data engineering consumers, including training and feature data delivery.
• Operate a platform whose data feeds billing or externally reported figures.

Benefits

• Incentive compensation, bonus, and restricted stock units may be offered in addition to base pay.
• F5 offers benefits; details are available through the benefits link in the posting.
• Continuous learning opportunities and mentorship.
• Reasonable accommodations are available for candidates.

What This Job Offers

• Job Type: Full-time
• Career Level: Director
• Education Level: No Education Listed