Technical Lead

Job Summary

Our client is a global leader in agricultural solutions, focused on seeds, traits, crop protection, and digital farming technologies that help growers increase yield, manage risk, and farm more sustainably. Its commercial model—especially in North America—is** dealer‑led**, requiring tight coordination across marketing, sales, dealers, and agronomy teams. Products are science‑intensive and decision‑sensitive, making consultative selling and field‑level trust critical. As a result, client relies heavily on data, analytics, and increasingly AI to deliver timely, compliant, and outcome‑driven customer experiences at scale.

Primary Focus

The team will build and operate a Marketing Automation Platform

that: - Drivesomnichannel, season‑aware marketing execution

• Supports agentic AI & A2A orchestration using** Google Gemini Enterprise**

• Integrates

marketing, sales, dealer activation, and CX Role: AI Engineer – Agentic AI & Gemini Role Summary

The AI Engineer will design, develop, and operationalize agentic AI capabilities using Google Gemini and Vertex AI, enabling intelligent marketing decisions, agent‑to‑agent orchestration (A2A), and closed‑loop learning for Client’s Crop Science domain.

This role blends ML engineering, LLM reasoning, and domain‑aware solutioning for regulated, real‑world agricultural use cases.

Key Responsibilities

Key Responsibilities

• Build Gemini‑powered AI agents (e.g., campaign recommendation, grower readiness, channel optimization).

• Implement A2A orchestration patterns (agents calling other agents, escalation logic, confidence thresholds).

• Ground LLM outputs using enterprise data (Big Query, Feature Store, CDP).

• Embed regulatory guardrails using policy‑aware prompting, validation layers, and agent gating.

Skill Requirements

Required Skills & Experience

• 5+ years in ML/AI engineering with at least 2+ years in LLMs or GenAI.

• Hands‑on experience with Vertex AI, Gemini, or comparable LLM stacks.

• Strong Python, API‑based architectures, async workflows.

• Experience with RAG, tool calling, agent frameworks, and ML pipelines.

• Familiarity with regulated domains (life sciences, agri‑tech, finance preferred).

Nice to Have

• Experience in agriculture, supply chain, or B2B marketing tech.

• Knowledge of Big Query ML, Feature Store, or Looker APIs.

• Experience building explainable or auditable AI systems.

Other Requirements

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