AI Engineer – Agentic AI / LLM / RAG

Job Overview

We are looking for an experienced AI Engineer to design, develop, and implement production-ready AI applications and intelligent agent-based solutions. The ideal candidate will have strong software engineering skills and hands-on experience developing LLM-powered applications, conversational AI solutions, and agentic workflows.

This role focuses on building and deploying practical AI solutions that integrate Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), vector databases, and backend services to solve real-world business challenges.

Candidates should have hands-on experience with Google Agent Development Kit (ADK) and developing AI agents or chatbot applications in production environments.

Key Responsibilities

• Design, develop, and deploy AI-powered applications using modern LLM APIs and agentic frameworks.

• Build intelligent AI agents and multi-step workflows to support business use cases.

• Develop and implement RAG pipelines using embeddings, vector databases, and semantic search.

• Integrate LLM-based capabilities into existing backend applications, APIs, and microservices.

• Develop conversational AI solutions and chatbot applications with context-aware responses.

• Design and optimize prompts to improve response accuracy, consistency, and overall LLM performance.

• Implement guardrails and validation mechanisms to minimize hallucinations and improve AI output quality.

• Optimize AI applications for performance, scalability, reliability, and response latency.

• Monitor, troubleshoot, and enhance AI solutions deployed in production environments.

• Collaborate with product and engineering teams to deliver scalable, reliable AI solutions.

Required Skills & Qualifications

• Strong hands-on software engineering experience developing and delivering production-grade applications.

• Practical experience building Agentic AI applications, AI agents, or LLM-powered chatbots.

• Hands-on experience with Google Agent Development Kit (ADK) for building agent-based applications.

• Strong programming skills in Python or a comparable backend programming language.

• Experience integrating LLM APIs and working with Large Language Models (LLMs).

• Hands-on experience implementing Retrieval-Augmented Generation (RAG) architectures.

• Knowledge of embeddings, semantic search, and vector databases such as Pinecone, Weaviate, FAISS, or similar.

• Experience with REST APIs, microservices, and distributed application architectures.

• Strong understanding of prompt engineering, prompt evaluation, and LLM behavior.

• Ability to troubleshoot, optimize, and maintain AI applications in production environments.

Preferred Qualifications

• Experience with agentic AI frameworks such as LangChain and Google ADK.

• Exposure to multi-agent architectures and workflow-driven AI applications.

• Experience with LLM fine-tuning, model customization, or optimization.

• Familiarity with cloud platforms such as AWS, Google Cloud Platform, or Azure.

• Experience working with structured and unstructured data pipelines.

• Understanding of AI application security, reliability, and operational best practices.

Additional Requirements

• Strong problem-solving and analytical skills.

• Ability to work independently and collaborate effectively with cross-functional teams.

• Comfortable working in a fast-paced engineering environment.

• Must be willing to work in a hybrid environment in Houston, TX.