Sr AI Engineer

Location: United States (Florida -Tampa)

Syniverse is the world’s most connected company. Whether we’re developing the technology that enables intelligent cars to safely react to traffic changes or freeing travelers to explore by keeping their devices online wherever they go, we believe in leading the world forward.Which is why we work with some of the world’s most recognized brands. Eight of the top 10 banks. Four of the top 5 global technology companies. Over 900 communications providers. And how we’re able to provide our incredible talent with an innovative culture and great benefits.

Who We're Looking For

Syniverse is scaling AI capability across the company, and this role is responsible for turning that strategy into working, production-grade systems. The Sr AI Engineer takes the patterns and standards set by the AI Architect and implements them as integrations, agentic automations, internal tooling, and the evaluation harnesses that measure whether each capability is actually performing as intended.

This is a hands-on-keyboard role. The engineer will spend most of their time writing code, debugging integrations, and shipping capability that colleagues across the company use daily.

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Some of What You'll Do

• Design, build, and maintain AI-powered integrations, agentic automations, and internal tooling on Syniverse's AI stack (Azure OpenAI, Claude Enterprise, and self-hosted models on AWS/EKS behind the Bifrost AI Gateway).
• Develop production-grade Retrieval-Augmented Generation (RAG) pipelines and Model Context Protocol (MCP) servers/tools that connect internal data and systems to LLMs.
• Build and maintain evaluation harnesses and test suites that measure model and system quality, catch regressions and drift, and report objectively on whether a given AI capability is working.
• Take architectural patterns and standards defined by the AI Architect and turn them into working, supported, production systems — not just proof of concept.
• Write, test, and ship code (primarily Python, Java, and SQL) implementing new AI capability and integrations end to end.
• Debug and troubleshoot issues across the AI stack — API layers, the AI gateway, model endpoints, and downstream integrations — including root-cause analysis of production issues.
• Evaluate tradeoffs between frontier LLMs and locally hosted models (e.g., Qwen, Gemma) and select the model best suited to a given requirement based on cost, latency, accuracy, and data sensitivity.
• Use agentic software development tools (Claude Code preferred; Codex or Cursor as viable alternatives) to build and ship production applications.
• Automate deployment, infrastructure, and operational tasks using DevOps tooling such as Ansible and Terraform, primarily on AWS.
• Create design documentation for new integrations and automations, and maintain operational runbooks for systems in production.
• Review code, designs, and evaluation results from peers to ensure accuracy, completeness, and adherence to requirements and standards.
• Partner cross-functionally across business units to gather requirements, integrate AI capability into existing workflows, and support adoption.
• Report on the status, metrics, and outcomes of AI initiatives to stakeholders and leadership.