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.