What you’ll be doing...

As an AI Engineer - Platform Engineering, you will serve as a core contributor to Verizon’s enterprise AI Platform—the mission-critical infrastructure facilitating intelligent request routing across the Consumer, Business, and Global Network & Technology (GN&T) organizations.

You will be responsible for the end-to-end lifecycle of 3–5 production services, encompassing architectural design, implementation, deployment, monitoring, and iterative enhancement, including participation in the technical on-call rotation.

This role requires a results-oriented engineer dedicated to delivering high-impact solutions, including intelligent model routing, the Verizon Agent SDK, Model Context Protocol (MCP) integrations, robust evaluation pipelines, and the DevSecOps automation necessary to ensure secure and reliable agent deployments.

You will be responsible for the following but not limited to:

• Building the AI Gateway. Develop model-agnostic routing services across Google Vertex (Gemini), AWS Bedrock (Claude), OpenAI, and open models (Phi, Gemma). Implement health-aware load balancing, automatic failover, cost-performance routing, JWT authentication, multi-tenant routing, rate limiting, and quota enforcement. Build token management services (pre-request estimation, post-response logging, per-BU cost attribution via PostgreSQL and BigQuery). 

• Contributing to the Agent Development Platform. Build core modules of the Verizon Agent SDK (Python primary, TypeScript secondary) with pre-integrated LLMOps, FinOps, logging, memory, and MCP tool gateway. Deliver Agent Registry components — registration, versioning, capability discovery, lifecycle management, Agent Card schema. Build MCP Tool Gateway integrations: translation layer, Apigee connectivity, output validation, chain-of-thought tracing per tool call. 

• Owning platform reliability, SLOs, alerting, runbooks, and incident response for your services (MTTD <15 min, MTTR <60 min). Write IaC (Terraform/Pulumi) for K8s cluster provisioning across GCP and AWS. Build ETL/CDC pipelines from per-namespace PostgreSQL to BigQuery/Athena for usage analytics and FinOps dashboards. Participate in on-call rotation. 

• Shipping continuous evaluation and DevSecOps. Building the Agent DevSecOps pipeline: ArgoCD deployment manifests, canary rollout controllers (5% → 25% → 100%), and auto-rollback triggers on accuracy dips or error spikes. Implement continuous evaluation pipelines: automated benchmarking, simulation harnesses, and RLAIF feedback loops. 

What we’re looking for…

AI Engineer with a track record of maintaining high-availability services and establishing robust operational frameworks. You possess deep expertise in large language model (LLM) infrastructure, transitioning complex research into scalable production environments with maintainable, high-quality code, with a strong commitment to developer experience, you ensure that SDKs and APIs are intuitive, versioned, and resilient. You are highly proficient in Kubernetes and multi-cloud architectures, demonstrating the strategic judgment to determine when to build internal solutions versus leveraging third-party platforms.

You’ll need to have:

• Bachelor’s degree or four or more years of work experience.

• Four or more years of relevant experience required, demonstrated through work experience and/or military experience.

• Experience in Python programming (production-grade code, testing, packaging).

• Experience insoftware engineering with production systems at scale.

• Experience with LLM or AI infrastructure — model serving, inference APIs, or agent frameworks.

• Experience with Kubernetes: deployments, services, ingress, HPA, secrets.

• Experience with API design: REST/gRPC, JWT/OAuth2, rate limiting, versioning.

• Experience with cloud platforms (GCP and/or AWS): compute, networking, IAM, managed databases.

• Experience with PostgreSQL and Redis in production.

• Experience with CI/CD tooling: GitHub Actions, ArgoCD, Docker.

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

• A Master’s degree in Computer Science or AI/ML.

• Experience with LLM serving frameworks (LLM Gateway, vLLM, TrueFoundry).

• Experience with distributed systems patterns: eventual consistency, idempotency, circuit breakers, retry with backoff.

• Experience with TypeScript or Go in production.

• Experience with Istio service mesh (VirtualService, mTLS).

• Experience building developer tools — SDKs, CLIs, or developer portals.

• Experience with agentic AI patterns (ReAct, tool calling, multi-agent orchestration).

• Experience with MCP (Model Context Protocol) — MCP servers, tool schema design.

• Experience with OpenTelemetry observability.

• Experience with CDC/ETL tooling (Debezium, BigQuery).

• Experience with security engineering (zero-trust, SPIFFE/SPIRE, OPA).

• Certifications: CKA/CKAD, AWS or GCP Cloud certifications.

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.

Our benefits are designed to help you move forward in your career, and in areas of your life outside of Verizon. From health and wellness benefit options including: medical, dental, vision, short and long term disability, basic life insurance, supplemental life insurance, AD&D insurance, identity theft protection, pet insurance and group home & auto insurance. We also offer a matched 401(k) savings plan, up to 8 company paid holidays per year and up to 6 personal days per year, paid parental leave, adoption assistance and tuition assistance, plus other incentives, we’ve got you covered with our award-winning total rewards package. Depending on the role, employees have the opportunity to receive compensation in the form of premium pay such as overtime, shift differential, holiday pay, allowances, etc. Newly hired employees receive up to 15 days of vacation per year, which grows with additional service. For part-timers, your coverage will vary as you may be eligible for some of these benefits depending on your individual circumstances.