Agentic AI Engineer

Agentic AI Engineer

We are seeking an Agentic AI Engineer to architect and implement autonomous, multi-agent workflows that go beyond static text generation. You will be responsible for building reliable agentic systems that interface with enterprise databases, execute real-world APIs, manage long-term state, and operate safely within strict performance and governance guardrails. You will be responsible for the following but not limited to:

• Agent Architecture & Orchestration: Design stateful, multi-step agentic workflows using reasoning frameworks (e.g., ReAct, Plan-and-Solve, Reflection).
• Tool & API Integration: Build reliable execution layers connecting LLMs to external systems via REST APIs, database connectors, and protocol standards like Model Context Protocol (MCP).
• Context & Memory Management: Implement short-term and long-term memory architectures, state persistency, context window optimization, and hybrid RAG retrieval layers.
• Evaluation & Guardrails: Establish offline test sets () and real-time observability pipelines (using LLM-as-a-judge, trace analysis, and latency/cost monitoring) to prevent hallucinations, infinite loops, and unwanted drift.
• Production Deployment: Containerize and deploy multi-agent microservices using scalable async patterns, distributed queues, and fallback mechanisms.

What we're looking for

You thrive on creating smart, customer-centric solutions that simplify user interactions and deliver immediate answers. Your expertise allows you to build secure, scalable AI frameworks using established software engineering practices, ensuring smooth integration with downstream enterprise tools. As a trusted engineer, teams rely on you to navigate challenging obstacles in NLP, AI integration, and search relevance. By combining deep technical proficiency in AI with an analytical, collaborative mindset, you will directly enhance our user journey.

You'll need to have

• Bachelor's degree or four or more years of work experience. Four or more years of relevant experience required, demonstrated through one or a combination of work and/or military experience, or specialized training.
• Experience building Multi-Agent Systems with complex delegation models (human-in-the-loop escalation paths).
• Hands-on experience developing enterprise-grade agentic workflows, multi-agent topologies, and task orchestration pipelines using platforms such as LangGraph, Google ADK / CES, Sierra, Decagon, or similar
• Experience with Large Language Models (LLMs), prompt engineering, retrieval-augmented generation (RAG) architectures, and generative AI guardrails.

Even better if you have one or more of the following

• Bachelor's Degree in Computer Science, Computer Engineering, Artificial Intelligence, or a related technical field.
• Experience in programming in modern languages (Python, Java, NodeJS) for building custom fulfillment webhooks, microservices, and backend APIs.
• Experience implementing Vertex AI Search / Enterprise Search, grounding models, custom data store connectors, and tuning search relevance and rankings.
• Experience integrating Google AI solutions with non-Google enterprise architectures via REST/SOAP APIs, pub/sub messaging, and webhook integrations.
• Knowledge of contact center integrations (telephony adapters, CRM platforms like Salesforce/Genesys, and live agent hand-off protocols).

Where you'll be working

In this hybrid role, you'll have a defined work location that includes working from home and a minimum of three days per week in the office, which will be set by your manager. Employees are responsible for maintaining compliance with hybrid work policies.

Scheduled Weekly Hours

40

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