IT Application Support Specialist L2 (Agentic AI Engineer)

Key Responsibilities

Gemini Enterprise Agent Development

- Design, build, and own multi-agent solutions on Gemini Enterprise (formerly Agent space) — agent architecture, orchestration, task/tool design, and multi-turn conversation flows.

- Configure grounding, enterprise search, and data connectors so agents retrieve accurate, up-to-date, and properly-scoped information.

- Integrate Gemini models (via the Gemini API and/or Vertex AI) into agents and downstream applications, tuning prompts, context strategies, and tool/function calling for reliability.

- Design and productionize RAG pipelines and retrieval strategies that feed agent grounding sources.

- Continuously evaluate and iterate on agent quality — accuracy, relevance, latency, and cost — using structure devaluation frameworks.

AI Governance & Responsible Agent Operations

- Define and implement governance frameworks for Gemini Enterprise agents: access control, data permissions, usage policies, and approval workflows for new agents going into production.

- Build guardrails against hallucination, data leakage, prompt injection, and unauthorized data access across agents and connectors.

- Establish monitoring, logging, and audit trails for agent behavior, including token usage, response quality, and policy violations.

- Partner with security, legal, and compliance stakeholders to ensure agents meet data privacy, residency, and responsible-AI requirements.

- Create and maintain documentation, review checklists, and lifecycle standards (build → evaluate → approve →monitor → retire) for enterprise agents.

- Track Gemini model and Gemini Enterprise feature releases and assess their impact on existing agents and governance policies.

Cross-Functional Collaboration &Automation

- Work closely with data science, AI engineering, security, and business teams to translate use cases into governed, production-ready agents.

- Automate agent configuration, evaluation, and deployment workflows using Python and APIs/SDKs for Gemini Enterprise and Vertex AI.

- Build internal tooling and dash boards to give stakeholders visibility into agent inventory, usage, and governance status.

- Participate in code and design reviews, contributing to shared standards for agent development and governance.

Required Skills & Experience

- 7+ years of experience in AI/ML engineering, applied AI, or Gen AI platform roles, with hands-on ownership of agent or LLM-application development.

- Direct, hands-on experience building and configuring agents on Gemini Enterprise (or Agent space) — agent design, grounding, enterprise search, data connectors.

- Strong hands-on experience with Gemini models (via Gemini API or Vertex AI) — prompting, tool/function calling, context and RAG design.

- Practical experience implementing AI governance controls — access management, guardrails, evaluation frameworks, audit logging, and responsible-AI policies for LLM/agent systems.

- Solid understanding of LLM application patterns — RAG, embeddings, vector search, multi-agent orchestration.

- Solid Python programming skills for automation, evaluation tooling, and API integration.

- Ability to work cross-functionally with data science, security/compliance, and business stakeholders to govern and scale agent deployments.

- Working familiarity with Google CloudPlatform (GCP) — IAM, Cloud Storage, basic networking — sufficient to collaborate with platform/infrastructure teams.

Qualifications

Preferred / Nice-to-Have

- Google Cloud certifications(Professional Machine Learning Engineer, or Professional Cloud Architect).

- Experience with Terraform, Kubernetes(GKE), or CI/CD pipelines, for coordinating with platform/DevOps teams on agent infrastructure.

- Experience with monitoring/observability stacks (Cloud Monitoring, Prometheus, Grafana, Datadog).

- Familiarity with responsible-AI/model-risk frameworks applied to enterprise GenAI.

- Prior experience with other enterprise Gen AI /agent platforms (e.g., OpenAI, Anthropic, open-source LLM stacks) as a point of comparison.

Soft Skills

- Strong governance and risk mindset —able to balance agent capability with safety, compliance, and trust.

- Clear communicator who can translate technical agent behavior into business and compliance language.

- Comfortable operating in ambiguity, especially with fast-evolving Gemini features and emerging agent governance practices.

- Ownership mentality — from agent design through deployment, evaluation, and long-term governance.

Tech Stack Summary

Category

Tools / Technologies

Agent Development (Primary)

Gemini Enterprise (Agent space), Gemini Models, Vertex AI, Model Armor, Custom ADK agents, Agent designer

AI Governance

Evaluation frameworks, audit/logging tooling, responsible-AI guardrails, IAM/access policies

Retrieval & Data

RAG pipelines, enterprise search, data connectors, vector search

Languages

Python (primary), Terraform, JavaScript, Bash

Cloud Platform (Supporting)

Google Cloud Platform (GCP) — IAM, Cloud Storage, networking basics

Monitoring

Cloud Monitoring, Cloud Logging, Prometheus, Grafana