Artificial Intelligence Engineer - Hybrid in Dallas, TX - Direct Hire (NOT Contract)

AI Engineer – Generative AI & Agentic SystemsAre you passionate about building cutting-edge AI solutions that solve real-world problems? We’re seeking an experienced AI Engineer to design, develop, and scale advanced AI applications powered by LLMs, RAG architectures, and agentic systems. In this role, you’ll partner with product, design, and engineering teams to take AI concepts from ideation to production and deliver transformative user experiences.This is a hybrid role (2–3 days onsite weekly, including Tuesdays and Wednesdays).What You’ll Do:Design, build, and deploy Generative AI applications, conversational assistants, copilots, and intelligent agents using leading foundation models. Architect and implement agentic workflows including tool-calling, multi-step reasoning, and multi-agent orchestration. Develop and optimize RAG (Retrieval-Augmented Generation) pipelines using vector databases and enterprise knowledge sources. Engineer prompts, structured outputs, and guardrails to improve reliability, accuracy, and AI safety. Build scalable backend orchestration services and integrate AI capabilities into user-facing applications. Monitor, evaluate, and optimize AI systems for quality, latency, cost, and performance. Collaborate cross-functionally to define requirements, deliver technical solutions, and contribute to AI best practices. Requirements:5+ years of experience in Software Engineering and/or Data Science, including 3+ years focused on Generative AI/LLMs. Strong hands-on experience building production-grade AI applications. Expertise with Python for AI/ML, backend services, and data pipelines. Proficiency in JavaScript/TypeScript, SQL, and relational databases. Experience with LLM APIs, open-source models, and agentic frameworks such as LangChain, OpenAI Agents SDK, or Google ADK. Hands-on experience with RAG architectures, vector embeddings, and vector databases. Experience with cloud platforms (AWS, GCP, or Azure) and containerization tools such as Docker and Kubernetes. Knowledge of CI/CD pipelines, Git workflows, testing, and software engineering best practices. Strong communication skills with the ability to collaborate across technical and non-technical teams. Bachelor’s degree in Computer Science, Data Science, Machine Learning, or related field (or equivalent practical experience). Preferences:Experience with voice-enabled AI agents, multimodal AI, or real-time conversational systems. Familiarity with AI evaluation frameworks, observability tools, and experiment tracking. Experience with MLOps, feature stores, or data versioning tools. Knowledge of AI security, privacy, and compliance practices (PII, SOC2, GDPR). Experience with browser automation tools such as Playwright. Familiarity with A/B testing and experimentation for AI-driven features. Why Join Us?You’ll work on innovative AI initiatives at the forefront of agentic AI, generative applications, and intelligent automation, helping shape next-generation user experiences in a collaborative and fast-moving environment.