Agentic AI Engineer

Robotics Technologies LLC; California; On-site; USD 140,000 - 220,000; Full time

Job summary

Robotics Technologies LLC is hiring for an enterprise AI agent engineer who will design and implement multi‑agent workflows and governed tool integrations. You will translate business cases into agentable solutions, build modular Python components, and ensure secure, scalable deployments.

You will work with Google ADK, Vertex AI, and Gemini, crafting prompts, embedding strategies and RAG pipelines, while enabling A2A collaboration and production‑readiness.

Qualifications

• Experience building enterprise AI agents and multi‑agent workflows.
• Ability to translate business use cases into agentic solutions.
• Familiarity with agent frameworks and secure data handling.

Responsibilities

• Design and build enterprise AI agents and interoperable multi‑agent workflows.
• Develop agent workflows using Google ADK and Vertex AI / Agent Engine.
• Use Gemini models for reasoning and structured outputs; craft prompts and templates.
• Implement RAG with embeddings and retrieval; manage session context and memory patterns.
• Integrate agents with MCP tools, REST APIs and external AI services.
• Design A2A collaboration including discovery, capability exchange and task delegation.
• Implement orchestration, multi‑step execution and human‑in‑the‑loop checkpoints.
• Apply input/output validation, guardrails and secure handling of sensitive data.
• Build modular Python components; support deployment and troubleshooting.
• Hands‑on exposure to A2A‑compatible agents or multi‑agent workflows.
• Familiarity with vector databases, knowledge graphs and related tech.
• Awareness of Model Armor and Responsible AI controls.

Skills

Python

AI agent development

LLM/Gen AI

A2A patterns

REST APIs

GCP

CI/CD

Docker

Tools

Google ADK

Vertex AI

Agent Engine

Gemini

BigQuery

AlloyDB

Vertex AI Search

Job description

US Citizen, Green Card, H-1B, OPT-EAD, CPT, Other

Job Description

• Strong Python development skills and hands‑on experience with LLM or Generative AI applications.
• Practical knowledge of agentic patterns: reasoning, orchestration, tool calling and workflow execution.
• Experience with Google ADK, Vertex AI, Agent Engine and Gemini, or comparable agent frameworks with ability to transition to this stack.
• Understanding of Agent‑to‑Agent (A2A) architecture and multi‑agent patterns, including agent discovery, capability exchange, task lifecycle, asynchronous interactions and secure context handoff.
• Understanding of RAG, embeddings, vector search, chunking, grounding and retrieval evaluation.
• Understanding of context and memory management for conversational and multi‑agent applications.
• Experience consuming REST APIs and integrating external services; familiarity with MCP for agent‑to‑tool connectivity.
• Working knowledge of GCP, Git/GitHub, Docker or containers, CI/CD and automated testing.

Roles & Responsibilities

Design and build enterprise‑grade AI agents and interoperable multi‑agent workflows using modern agentic AI frameworks. Translate defined business use cases into agents that can reason, use governed enterprise knowledge, maintain context, invoke approved tools and APIs, and collaborate with other agents through Agent‑to‑Agent (A2A) patterns. Contribute to rapid pilots and production‑ready implementations using reusable platform capabilities.

• Design and develop enterprise AI agents based on defined business workflows and acceptance criteria.
• Build agent workflows using Google ADK and Vertex AI / Agent Engine.
• Use Gemini models for reasoning, planning, summarization and structured response generation.
• Develop prompts, prompt templates and structured outputs; support prompt testing and evaluation.
• Implement RAG capabilities using approved enterprise knowledge sources, chunking, embeddings and retrieval.
• Implement session context, short‑term memory and long‑term memory patterns where required.
• Integrate agents with approved MCP tools, REST APIs and external AI services.
• Design agent‑to‑agent collaboration using A2A patterns, including agent discovery, capability definition, task delegation, context exchange, status handling and response coordination.
• Implement orchestration, tool selection, multi‑step execution and human‑in‑the‑loop checkpoints across single‑agent and multi‑agent workflows.
• Apply input/output validation, guardrails and secure handling of sensitive information.
• Build modular, reusable and testable Python components; support deployment and operational troubleshooting.
• Hands‑on exposure to implementing A2A‑compatible agents or interoperable multi‑agent workflows.
• Exposure to BigQuery, AlloyDB, Vertex AI Search, vector databases or knowledge graphs.
• Familiarity with Model Armor, AI guardrails, Responsible AI controls, IAM, RBAC or ABAC.
• Experience taking an AI proof of concept through pilot deployment and production readiness.

We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.