AI Agent Engineer

ChaiOne • Houston, TX

18h

About The Position

The Lead AI Engineer owns the architecture, development, and deployment of production-grade AI agent systems spanning language, voice, vision, and automation. The position combines hands-on engineering with strategic technical leadership, turning emerging AI capabilities into reliable systems that address business needs.

The role designs AI-powered workflows combining LLMs, APIs, multimodal models, automation platforms, and conversational interfaces. It sets technical direction, standards, and best practices for AI development, and helps build dependable infrastructure for responsible and effective AI use across the organization.

Requirements

• At least 6 years of software engineering experience, with a deep focus on applied AI systems.
• Strong experience working with LLMs and AI APIs such as OpenAI, Anthropic, Google, or similar.
• Proven experience building production AI systems, not just prototypes.
• Strong programming skills in Python and/or JavaScript/TypeScript.
• Experience with APIs, microservices, and backend integrations.
• Strong understanding of system reliability, scalability, and observability.
• Excellent communication skills and ability to explain complex systems clearly.

Nice To Haves

• Experience with agent frameworks such as LangChain, LangGraph, AutoGen, or CrewAI.
• Experience building voice agents or conversational AI systems.
• Experience with computer vision or multimodal models.
• Familiarity with no-code or low-code automation tools such as n8n or Zapier.
• Experience working in small, fast-moving teams or startups.

Responsibilities

• Design and implement scalable AI agent architectures using LLMs, tool calling, retrieval, memory, and orchestration frameworks.
• Own multi-step and multi-agent workflows for complex tasks and decision-making.
• Determine when to use LLM-based approaches versus deterministic systems.
• Lead prompt strategy across GPT-4, Claude, Gemini, and open-source models; develop reusable prompt patterns, chains, and templates; and optimize prompts for reliability, safety, latency, and cost.
• Architect and build end-to-end AI workflows using tools such as n8n, LangGraph, AutoGen, or custom orchestration layers.
• Integrate AI agents with backend systems, including CRMs, databases, internal tools, and third-party APIs.
• Implement error handling, retries, observability, and logging.
• Lead the design of production-grade voice agents and conversational systems, including dialogue, intent handling, fallback strategies, and escalation paths.
• Ensure compliance, safety, and reliability in voice and conversational use cases, and optimize for low latency, natural language flow, and user trust.
• Design and deploy multimodal workflows combining vision, language, and automation.
• Apply vision models to use cases such as object detection, quality control, and document understanding, and integrate vision outputs into downstream agent decisions.
• Define evaluation frameworks for AI output accuracy, hallucination risk, safety, and bias.
• Build automated testing and QA pipelines for agent systems; monitor production performance and continuously improve systems.
• Set technical standards and best practices for AI development.
• Mentor interns and junior engineers on AI workflows and engineering rigor.
• Collaborate with Product, Design, and Enablement teams to translate business needs into AI solutions.

Benefits

• Ownership of cutting-edge AI systems from concept to production.
• Opportunity to define and scale an AI agent platform.
• Direct impact on product direction and business outcomes.
• Leadership growth through mentoring and technical decision-making.
• Competitive compensation and growth opportunities; details shared during the process.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed