AI Engineer

About the role

We are seeking a highly skilled and forward-thinking Senior AI Engineer to lead the architecture, scalability, and integration of our enterprise agentic AI platforms. In this role, you will design and deploy autonomous multi-agent workflows capable of executing complex reasoning loops, tool usage, and cross-platform collaboration. The ideal candidate bridges the gap between cutting-edge agentic frameworks and robust production-grade software engineering. You will leverage Google Cloud’s Gemini Enterprise Agent Platform (formerly Vertex AI) to build secure, scalable, and highly optimized AI pipelines.

Responsibilities

• Agentic Architecture & Application Development: Design and build production-grade Python applications using advanced orchestration frameworks like LangChain, LangGraph, and CrewAI to manage autonomous multi-agent systems, stateful reasoning, and complex RAG (Retrieval-Augmented Generation) workflows.
• GCP Agent Platform Infrastructure: Deploy, scale, and govern AI agents leveraging the full Gemini Enterprise Agent Platform (Vertex AI Agent Builder ecosystem), including the Agent Development Kit (ADK) for code-first deployment, Agent Engine for stateful runtimes, and Agent Studio for prototyping.
• Tool Protocol Integration: Enable inter-agent collaboration and data access by implementing the Agent2Agent (A2A) protocol and Model Context Protocol (MCP), connecting agentic workflows securely to enterprise databases, remote MCP servers, and third-party workflow APIs.
• AI Engineering & Token Optimization: Actively monitor, profile, and optimize LLM prompt structures, context windows, and caching mechanisms to maximize agent reasoning efficiency while minimizing token consumption and operational costs.
• Grounding Knowledge Architecture: Design and maintain hybrid search structures using Vertex AI Vector Search and Vertex AI Search to ground agent decisions in authoritative enterprise data, local files, and external specialized data sources.
• Enterprise Security & Compliance: Architect decentralized agent systems under zero-trust principles. Enforce robust data privacy protocols using Vertex AI Model Armor to prevent prompt injections and manage permissions securely via Agent Identity and Google Cloud IAM.
• DevOps & Agent Observability: Establish and maintain robust CI/CD pipelines to automate the testing, versioning, and deployment of agentic systems. Utilize Vertex AI Agent Engine Runtime tracing, logging, and Unified Trace Viewers to debug complex agent reasoning loops in production.

Requirements

• Core Programming: Strong mastery of Python and standard enterprise software design patterns.
• Agentic Orchestration: Deep hands-on experience building complex, production-ready agentic workflows with LangChain, LangGraph, CrewAI, or Google’s native Agent Development Kit (ADK).
• Google Cloud (GCP): Proven expertise with Gemini Enterprise Agent Platform, Vertex AI Agent Builder, GKE (Google Kubernetes Engine), Cloud Run, and IAM.
• Protocols & Standards: Familiarity with modern agentic communication standards like Model Context Protocol (MCP) and Agent2Agent (A2A) protocols.
• Databases & Vector Search: Strong understanding of Vertex AI Vector Search or standalone vector databases for semantic search, metadata filtering, and embedding lifecycle management.
• DevOps & MLOps: Proficiency with modern CI/CD tools (e.g., GitHub Actions, GitLab CI) and containerization (Docker/Kubernetes).

Qualifications

• 5+ years of software engineering experience, with at least 2–3 years dedicated to building and deploying AI/LLM-powered applications and agentic systems at an enterprise scale.
• Bachelor’s or Master’s degree in Computer Science, AI, Data Science, or a related technical field, or equivalent practical experience.

Schedule

3 days hybrid (Southlake, TX).

Pay

The range displayed reflects the minimum and maximum salary target for the position across all US locations. Within the range, individual pay is determined by work location, job level, and additional factors including job-related skills, experience, and relevant education or training. Depending on the position, other forms of compensation may be provided, such as an annual performance-based bonus, sales incentive pay, or other forms of bonus/variable compensation.

Benefits

• Comprehensive medical plan covering medical, dental, and vision.
• Short-term and long-term disability coverage.
• 401(k) plan with company match.
• Life insurance.
• Vacation time, sick leave, and paid holidays.
• Paid paternity and maternity leave.