Associate Director - AI Platform Engineering

When you join Verizon

You want more out of a career. A place to share your ideas freely — even if they’re daring or different. Where the true you can learn, grow, and thrive. At Verizon, we power and empower how people live, work and play by connecting them to what brings them joy. We do what we love — driving innovation, creativity, and impact in the world. Our V Team is a community of people who anticipate, lead, and believe that listening is where learning begins. In crisis and in celebration, we come together — lifting our communities and building trust in how we show up, everywhere & always. Want in? Join the #VTeamLife.

What you’ll be doing…

You’ll lead engineering delivery for two foundational pillars of Verizon’s enterprise AI Platform — the Adaptive Intelligence Gateway that routes every AI request across all business units and the Agent Development Lifecycle (ADLC) that governs how AI agents are built, registered, and deployed. You’ll manage a team of 3–5 engineers, own the engineering roadmap, and translate platform architecture into production-grade services that thousands of Verizon developers depend on.

• Owning AI Gateway engineering. Design and deliver intelligent model routing, multi-provider failover (Google Vertex, AWS Bedrock, OpenAI), per-BU FinOps and chargeback, semantic caching, and self-service tenant onboarding on a Kubernetes/Istio foundation with JWT-driven multi-tenant namespace isolation.
• Delivering the Agent Development Lifecycle. Ship the Agent Registry with zero-trust identity (SPIFFE/SPIRE), the Verizon Agent SDK with pre-integrated LLMOps/FinOps/guardrails, the MCP Tool Gateway, and an ArgoCD-managed DevSecOps pipeline with canary deployments and auto-rollback.
• Hitting the SLAs that keep the platform trusted. 99.9% Gateway uptime, ≤2,000ms P95 latency, Mean Time to Agent Deploy reduced from 21 days to ≤7 days, 95%+ Agent & Registry Compliance.
• Driving enterprise consolidation and cost control. Consolidate 8+ independent BU AI integrations onto one managed gateway, enable real-time cost attribution, and unlock $500K+ quarterly optimization savings through intelligent routing.
• Onboarding the business. Land 5+ BU teams on the platform within 6 months, ship Agent Registry GA and SDK v1.0, and establish the engineering operating cadence with Architecture, Operations, and BU consumers.
• Leading the team. Recruit, coach, and grow a team of 3–5 platform engineers; set the engineering bar, review designs, and remove blockers so the team ships.

What we’re looking for…

You’ll need to have:

• Bachelor’s degree or four or more years of work experience.
• Eight or more years of relevant experience required, demonstrated through one or a combination of work and/or military experience, or specialized training.
• Technical leadership experience managing software or platform engineers.
• Experience running Kubernetes at production scale.
• Experience operating in multi-cloud environments (GCP and AWS).
• Experience with AI/ML infrastructure: model serving (vLLM, LLM Gateways,  or equivalent), inference optimization, and LLMOps.
• Experience building developer platforms — SDKs, CLIs, developer portals, or self-service onboarding.
• Experience with FinOps or cost allocation models (chargeback, budget enforcement, usage attribution).

Even better if you have one or more of the following:

• A Bachelor’s or Master’s degree in Computer Science, Engineering, or an MBA.
• Experience with API gateway patterns: JWT authentication, rate limiting, traffic splitting, circuit breakers, and mTLS
• Software or platform engineering experience.
• Experience with agentic AI frameworks (LangGraph, Google ADK, CrewAI, or similar).
• Familiarity with MCP (Model Context Protocol) and A2A (Agent-to-Agent) standards.
• Experience implementing zero-trust security (SPIFFE/SPIRE, OPA/Rego).
• Experience with CDC pipelines and event-driven data platforms (BigQuery, Kafka).
• Experience delivering platforms in a telecom or large regulated enterprise (CPNI, PCI-DSS, SOX).
• Experience designing Responsible AI guardrails, evaluation pipelines, or model governance.
• Experience with observability stacks (Jaeger, Prometheus/Grafana, ELK, or BigQuery-based).
• Certifications: AWS Solutions Architect, GCP Professional Cloud Architect, CKA/CKAD.

If Verizon and this role sound like a fit for you, we encourage you to apply even if you don’t meet every “even better” qualification listed above.

Where …