Lead AI Engineer

We are seeking an AI leader to spearhead the design of next-generation agentic workflows and manage a high-performing engineering team. You will drive technical strategy for multi-agent systems on GCP, while mentoring engineers to deliver production-grade AI solutions. A critical component of this role involves providing technical guidance and direct mentorship to our junior AI Engineers to elevate the team's overall capabilities. Additionally, you will directly engage with external clients to translate complex business challenges into cutting-edge AI solutions, acting as the primary technical point of contact and trusted advisor.

Key Responsibilities

• Team Leadership & Mentorship: Lead, mentor, and scale a team of AI and software engineers, specifically guiding and mentoring junior AI engineers in best practices for agentic development.
• Client Engagement & Strategy: Act as the primary technical interface for clients, leading technical discovery sessions, gathering business requirements, and translating client objectives into production-ready architectures.
• Delivery Management: Oversee sprint planning, code reviews, and cross-functional technical alignment to ensure client deliverables are met on time and to high technical standards.
• Agentic Architecture: Design scalable, event-driven, multi-agent AI ecosystems on GCP utilizing the code-first Agent Development Kit (ADK).
• Advanced LLM Integration & Evaluation: Build advanced agentic logic using Google Gemini models and the unified Gemini Enterprise Agent Platform. Develop sophisticated prompting strategies (ReAct, CoT) and performance evaluation frameworks utilizing the Agent Engine Evaluation Layer to demonstrate system reliability to clients.
• Tooling & Enterprise RAG: Implement advanced RAG pipelines using Vertex AI Search and the Agentic Data Cloud. Connect agents securely to BigQuery, Cloud SQL, and APIs while managing persistent state and context with the Agent Platform Memory Bank.
• Deployment & Scaling: Containerize and deploy production microservices using Agent Engine and Cloud Run, or self-hosted Agent Sandbox on GKE. Enforce input/output safety using Model Armor and secure traffic with the Agent Gateway to satisfy strict client security and governance requirements.

Minimum Qualifications

• Education: Bachelor's degree in Computer Science, Engineering, or equivalent practical experience.
• Leadership & Client Experience: 2+ years of experience leading engineering teams or technical projects, with a proven track record of direct client interaction, consulting, or technical account management.
• Communication Skills: Exceptional communication and presentation skills, with the ability to articulate deeply technical AI concepts to both engineering teams and non-technical client stakeholders.
• Core Engineering: Expert-level Python proficiency and solid software engineering practices (CI/CD, Git, automated testing), with additional familiarity in Go, Java, or TypeScript for comprehensive ADK implementations.
• Cloud Infrastructure: Proven hands-on experience building, deploying, and managing applications on GCP.
• LLM Production Experience: Demonstrable history of shipping applications using LLMs, specifically Gemini models, and modern agentic frameworks such as the Google ADK.

Preferred Qualifications

• Advanced Degree: Master's or PhD in Computer Science, AI, or Machine Learning.
• Platform Expertise: Deep knowledge of the Gemini Enterprise Agent Platform, driving the transition beyond legacy pipelines to modern agent-centric observability and governance tools.
• Advanced Orchestration: Success building large-scale, self-correcting, multi-step agents that plan autonomously.
• Infrastructure at Scale: Experience with Agent Engine, Cloud Run, and event-driven messaging (Pub/Sub).
• Certifications: Google Cloud Professional Cloud Architect or Machine Learning Engineer credentials.