AI Engineer – Agentic AI &

- Gemini

Experience: 2 to Not Available years

Location: Bengaluru, India

Skills: ML/AI engineering, LLMs, GenAI, Vertex AI, Google Gemini, Python, API-based architectures, async workflows, RAG, tool calling, agent frameworks, ML pipelines, BigQuery, Feature Store, CDP

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:

Drives omnichannel, 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

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 (BigQuery, 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.

Solid 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 BigQuery ML, Feature Store, or Looker APIs.

Experience building explainable or auditable AI systems.

Other Requirements null

📌 AI Engineer – Agentic AI & Gemini (India)
🏢 HCL Technologies
📍 India