Associate Director - AI Platform Engineering
About The Position
Lead engineering delivery for two foundational pillars of Verizon’s enterprise AI Platform: the Adaptive Intelligence Gateway, which routes AI requests across business units, and the Agent Development Lifecycle (ADLC), which governs how AI agents are built, registered, and deployed. Manage a team of 3–5 engineers, own the engineering roadmap, and turn platform architecture into production-grade services used by Verizon developers. Design and deliver AI Gateway capabilities including intelligent model routing, multi-provider failover across Google Vertex, AWS Bedrock, and OpenAI, per-business-unit FinOps and chargeback, semantic caching, and self-service tenant onboarding on a Kubernetes/Istio foundation with JWT-driven multi-tenant namespace isolation. Deliver the Agent Registry with zero-trust identity, the Verizon Agent SDK with integrated LLMOps, FinOps, and guardrails, the MCP Tool Gateway, and an ArgoCD-managed DevSecOps pipeline with canary deployments and automatic rollback. Maintain platform service and delivery targets, including 99.9% Gateway uptime, P95 latency of no more than 2,000 ms, reducing Mean Time to Agent Deploy from 21 days to no more than 7 days, and achieving at least 95% Agent and Registry Compliance. Consolidate more than eight independent business-unit AI integrations onto one managed gateway, enable real-time cost attribution, and pursue quarterly optimization savings of more than $500,000 through intelligent routing. Onboard at least five business-unit teams within six months, launch the Agent Registry generally and SDK v1.0, and establish an engineering operating cadence with Architecture, Operations, and business-unit consumers. Recruit, coach, and develop a team of 3–5 platform engineers; set engineering standards, review designs, and remove blockers.
Requirements
- Bachelor’s degree or four or more years of work experience.
- Eight or more years of relevant experience, demonstrated through 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, including GCP and AWS.
- Experience with AI/ML infrastructure, including model serving (such as vLLM, LLM Gateways, or equivalent), inference optimization, and LLMOps.
- Experience building developer platforms such as SDKs, CLIs, developer portals, or self-service onboarding.
- Experience with FinOps or cost allocation models, including chargeback, budget enforcement, or usage attribution.
Nice To Haves
- Bachelor’s or Master’s degree in Computer Science or Engineering, or an MBA.
- Experience with API gateway patterns such as JWT authentication, rate limiting, traffic splitting, circuit breakers, and mTLS.
- Software or platform engineering experience.
- Experience with agentic AI frameworks such as LangGraph, Google ADK, or CrewAI.
- Familiarity with MCP (Model Context Protocol) and A2A (Agent-to-Agent) standards.
- Experience implementing zero-trust security, such as SPIFFE/SPIRE or OPA/Rego.
- Experience with CDC pipelines and event-driven data platforms such as BigQuery or Kafka.
- Experience delivering platforms in a telecom or large regulated enterprise, including CPNI, PCI-DSS, or SOX environments.
- Experience designing Responsible AI guardrails, evaluation pipelines, or model governance.
- Experience with observability stacks such as Jaeger, Prometheus/Grafana, ELK, or BigQuery-based observability.
- AWS Solutions Architect, GCP Professional Cloud Architect, CKA, or CKAD certification.
Responsibilities
- Lead engineering delivery for the Adaptive Intelligence Gateway and Agent Development Lifecycle.
- Manage a team of 3–5 platform engineers, including recruiting, coaching, and developing team members.
- Own the engineering roadmap and translate platform architecture into production-grade services.
- Design and deliver intelligent model routing, multi-provider failover, per-business-unit FinOps and chargeback, semantic caching, and self-service tenant onboarding.
- Build and operate the AI Gateway on Kubernetes/Istio with JWT-driven multi-tenant namespace isolation.
- Deliver the Agent Registry, Verizon Agent SDK, MCP Tool Gateway, and an ArgoCD-managed DevSecOps pipeline with canary deployments and automatic rollback.
- Meet platform targets for Gateway uptime, P95 latency, agent deployment time, and Agent and Registry compliance.
- Consolidate independent business-unit AI integrations onto a managed gateway and enable real-time cost attribution and optimization.
- Onboard at least five business-unit teams within six months, launch the Agent Registry GA and SDK v1.0, and establish an engineering operating cadence with Architecture, Operations, and business-unit consumers.
- Set engineering standards, review designs, and remove blockers so the team can deliver.
Benefits
- Medical insurance
- Dental insurance
- Vision insurance
- Short- and long-term disability insurance
- Basic and supplemental life insurance
- AD&D insurance
- Identity theft protection
- Pet insurance
- Group home and auto insurance
- Matched 401(k) savings plan
- Up to 8 company-paid holidays per year
- Up to 6 personal days per year
- Paid parental leave
- Adoption assistance
- Tuition assistance
- Incentives and other components of Verizon’s total rewards package
- Potential premium pay, such as overtime, shift differential, holiday pay, or allowances, depending on the role
- Up to 15 days of vacation per year for newly hired employees, increasing with service
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What This Job Offers
Job Type
Full-time
Career Level
Director
