AI Strategy Lead

JBS’s Gen AI practice is growing. We work with fortune 500s on their Agentic AI strategy, plans and execution. We deliver state of the art solutions like conversational commerce and skills architecture based agents. To support our growth we are seeking a

Technical Lead to work with our team and client on AI and digital transformation.

You will own the technical execution of the client's agentic AI initiative, coordinating a small team (2-3 people) across agent-based automation, platform orchestration, data layer integration, and cross-team architecture alignment. You will engage directly with the client's internal architects, platform teams, and business-side product owners.

What You Will Do

Coordinate a small team ( developers, BA) to execute on the agentic AI roadmap. Review output, ensure quality, assign priorities.

Engage directly with the client's internal technical teams. Participate in architecture discussions, contribute to design decisions, and help drive cross-team alignment.

Own the technical workstream: current-state documentation, future-state architecture options, API dependency mapping, orchestration analysis, and workshop materials.

Translate between technical teams and business stakeholders. Present options and trade-offs to directors with clarity.

Evaluate how AI agents should be designed, how they connect to business systems, and how they are managed in production. You make architecture recommendations, not write code.

Reduce load on client leadership by driving the initiative end to end.

Represent JBS at technology forums.

Required

5+ years in technology roles spanning architecture, solution design, delivery, or technical consulting.

1+ years coordinating or leading work across a small team (2-3 people). Formal management title not required.

Working knowledge of how AI agents are designed and deployed in enterprise environments. Can explain what an AI agent does, how it connects to tools and data sources, and how it is governed.

Can name and describe at least one agentic AI framework (LangChain, LangGraph, CrewAI, Google ADK, or similar) or LLM tool-use pattern (Claude, OpenAI function calling).

Google ADK experience is highly desired.

Clear communication. Can present to directors. Can work with developers. Can produce documents that non-technical stakeholders understand.

Self-directed. You get context and a problem, not a task list.

Comfortable operating inside someone else's organization as an embedded resource.

Preferred

Energy, utilities, or other regulated industry domain (financial services, healthcare, telecom).

GCP ecosystem experience including awareness of Google's AI agent capabilities.

Prior consulting or SI background.